Stanford Vision and Learning Lab @StanfordSVL Twitter profile

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Street View Image, Pose & 3D Cities Dataset. 25 million images, 3D models of 8 cities, camera pose & correspondences

GitHub - amir32002/3D_Street_View: The repo of Street View Image, Pose, and 3D Cities Dataset. Used...

The repo of Street View Image, Pose, and 3D Cities Dataset. Used in "Generic 3D Representation via Pose Estimation and Matching", ECCV16 - amir32002/3D_Street_View

github.com

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

#TransferLearning is crucial for general #AI , and understanding what transfers to what is crucial for #TransferLearning . Taskonomy ( #CVPR18 oral) is one step towards understanding transferability among #perception tasks. Live demo and more:

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Introducing the RoboTurk Real Robot Dataset - one of the largest, richest, and most diverse robot manipulation datasets ever collected using human creativity and dexterity! 111 hours 54 non-expert demonstrators 2144 demonstrations Download: [1/2]

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

Stanford Vision and Learning Lab is presenting 7 papers at #CORL2023 , including 3 oral presentations, and 3 award nominations, see below:

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

[1/2] Our lab has 3 papers accepted to NeurIPS 2019: 1. HYPE: Human Eye Perceptual Evaluation of Generative Models. Zhou and Gordon et al. (Oral) 2. SOCIAL-BIGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks. Kosaraju et al.

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Stanford Vision and Learning Lab: Performing Research at the Forefront of Computer Vision, Machine Learning, and Robotics - ⁦ @drfeifei ⁩ ⁦ @silviocinguetta ⁩ ⁦ @jcniebles ⁩

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Stanford Vision and Learning Group website is online now! @drfeifei @silviocinguetta @jcniebles

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

We are hosting one of the 3 challenges of at CVPR20. Train your navigating agent in our simulator Gibson () and we will test it in the real world! The best solutions will showcase live during CVPR. More info:

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Learning from hints (not demonstrations): A new paper on an important direction of RL for control where expert intuition can be used to guide learning without the need to provide optimal or even complete solutions.

Animesh Garg

@animesh_garg

5 years

Our new work at #Corl2019 will present RL with Ensemble of Suboptimal Teachers -aka- specify as much as you can easily, let learning handle the rest. Blog: Paper: w\ @andrey_kurenkov , A. Mandlekar, @RobobertoMM , @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Work from our group in Robot Learning for Manipulation is finalist for best paper award at @icra2019 and is being presented tomorrow in Montreal. @drfeifei @silviocinguetta @animesh_garg @yukez @michellearning @leto__jean

Animesh Garg

@animesh_garg

5 years

Excited to be at #ICRA2019 Best Paper Award talk Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks Paper: Video:

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Wiki: Paper and more details: [2/2]

Scaling Robot Supervision to Hundreds of Hours with RoboTurk:...

Large, richly annotated datasets have accelerated progress in fields such as computer vision and natural language processing, but replicating these successes in robotics has been challenging....

arxiv.org

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

We are happy to announce our ICCV19 Workshop on Visual Perception for Navigation in Human Environments: The JackRabbot Social Robotics Dataset and Benchmark. Submission deadline August 20. For more info, contact @SHamidRezatofig and Roberto Martin-Martin

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Stanford Vision and Learning Lab

@StanfordSVL

6 months

Are you a passionate and experienced researcher in robotics with knowledge in computer vision? Do you want to build impactful robotic systems? Stanford Vision and Learning lab (SVL) is searching for a Postdoctoral Fellow with your skills.

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Our focus on robot learning from single example of a task through a video has resulted in a line of work that combines symbolic systems with neural networks

Animesh Garg

@animesh_garg

5 years

This continues our efforts in neuro-symbolic planning for one-shot imitation in multi-step reasoning domains. 1. Neural Task Programs: 2. Neural Task Graphs: 3. Continuous Relaxation of Symbolic Planner:

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

The group wins the best paper award at #ICRA2019 for work on multimodal state representations in robot policy learning

Animesh Garg

@animesh_garg

5 years

We won the best paper award @michellearning @yukez @leto__jean @drfeifei @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

New work on pose tracking from our group

Yuke Zhu

@yukez

6 years

We have just released our new work on 6D pose estimation from RGB-D data -- real-time inference with end-to-end deep models for real-world robot grasping and manipulation! Paper: Code: w/ @danfei_xu @drfeifei @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

4 months

Stanford Vision and Learning Lab members and alumni: we are organizing a SVL+Alumni meet up at CVPR’24! Please check your emails for more details.

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Congrats @silviocinguetta for the appointment as the inaugural Mindtree Faculty Scholar at Stanford

Silvio Savarese

@silviocinguetta

6 years

I am delighted to share the news that I have been appointed the inaugural Mindtree Faculty Scholar at Stanford. More info:

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Check out New work from the group on task oriented grasping at #RSS18 by @KuanFangAI @yukez @animesh_garg @andrey_kurenkov @thebigmehtaphor @drfeifei @silviocinguetta

Animesh Garg

@animesh_garg

6 years

Check out our paper on Task-Oriented Grasping at #RSS2018 at 930am on Wed 06/27 (find full paper here: )

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

A new work on structuring diverse semantics in 3D space that yielded the 3D Scene Graph! It’s showcased on the Gibson database by annotating the models with diverse semantics using a semi-automated method.

Iro Armeni

@ir0armeni

5 years

What space should diverse semantics be grounded & what should be the structure? 3D Scene Graph is a 4-layer structure for unified semantics, 3D space &camera. We demonstrate it on Gibson models with an automated labeling method. Data available to download!

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

Composable Part-based Manipulation uses object-part decomposition & part-part correspondences to improve generalization of robotic manipulation across object categories. @Weiyu_Liu_ Poster: Thu 9 2:45-3:30 pm Website: w/ Tucker Hermans & @animesh_garg

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Thanks to @elonmusk for making time and @russelljkaplan , @shivon and @karpathy in making it happen

Russell Kaplan

@russelljkaplan

6 years

Fun chat last night at the Tesla party with Elon and some @StanfordCVGL folks #CVPR2018

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

This is continuing an important line of work in policy learning with large Datasets. More importantly this is the question to answer if we need to create a analog of "Imagenet" for Robotics. We need to both collect large Datasets and have Algorithms to leverage this data!

Animesh Garg

@animesh_garg

5 years

New work on exploring if a policy can be learned only from offline, off-policy dataset? IRIS: Implicit Reinforcement without Interaction at Scale Video: Seattle Robotics @NvidiaAI @AjayMandlekar @drfeifei B. Boots F. Ramos D. Fox

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Thanks a lot for the support @NvidiaAI

NVIDIA AI Developer

@NVIDIAAIDev

7 years

We did it again! Last night we handed out another 15 NVIDIA V100s to world smartest #AI researchers at #ICML2017

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Joint 2D-3D-Semantic data for scene understanding is out! 70K+ images and 6 mutually registered modalities in 2D&3D:

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Congratulations to Ashesh, Amir, Silvio and Ashutosh for the best student paper award at CVPR 2016!!Structural-RNN!!

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Continued efforts in larger scale crowdsourcing robotics for dataset creation in setups where engineered solutions are hard, simulation is tricky and pure compute has low success. The diversity of human cognitive reasoning and dexterity provides so many ways do do the same task!

Animesh Garg

@animesh_garg

5 years

Scaling crowdsourcing robotics with Human Reasoning & Dexterity for Large-Scale Dataset Creation Blog: Paper: Webpage: @AjayMandlekar @yukez @silviocinguetta @drfeifei J. Booher, M. Spero, A. Tung, A. Gupta

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

A thorough evaluation of possible action spaces and their efficiency with RL for manipulation tasks. The answer is best of both worlds - Op. Space control in end effector space with learnable gains fares better than end to end image-to-torque

Animesh Garg

@animesh_garg

5 years

Which control spaces work well for RL in contact-rich robot manipulation -- 'Variable Impedance Control in End-Effector Space' #IROS2019 Paper: Video: w\ Roberto M-M., @michellearning , R. Gardener, @silviocinguetta , @leto__jean

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Chris Choy

@ChrisChoy208

6 years

We created 4D ConvNets for 3D video perception :D Please checkout our paper: 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks, @cvpr2019

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

PhD student @lynetcha gives a great overview of ongoing work in point cloud segmentation

The TWIML AI Podcast

@twimlai

7 years

Be sure to check out #TWiMLTalk #123 ! Joined by @lynetcha , we discuss her work on SEGCloud, an end-to-end framework that performs 3D point-level segmentation. Head over to to listen!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

This is a very exciting new direction of research in our group: perception by combining vision with touch for manipulation.

Animesh Garg

@animesh_garg

6 years

Very excited to share our new paper on Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations. Featuring RL on real-robots from scratch in a matter of hours without any simulation! Video: arXiv:

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Thanks @ToyotaResearch and @SAILToyota for the exciting new experimental platform!

Animesh Garg

@animesh_garg

6 years

New baby rolls in SVL lab ( @StanfordCVGL ) - the @ToyotaResearch HSR. looking forward to servicing some humans! @drfeifei @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Semantic Segmentation of 3D Point Clouds #3DV @lynetcha , @ChrisChoy208 Iro Armeni, @JunYoungGwak , @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Congrats to all our graduates!

Fei-Fei Li

@drfeifei

6 years

Happy day for students, and proud day for advisor (i.e. me) and families on @Stanford Computer Science Dept Graduation Ceremony day :) Last picture is for CS231n instructors/TAs. @jcjohnss @syeung10 @cs231n

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Great work in policy learning for navigation using visual info @ICRA2017 @drfeifei

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

If you are at #CVPR18 , there is a workshop organized by Berkeley, Stanford, and MIT on Beyond Supervised Learning, with a great lineup of speakers. At Ballroom G. Drop by! #perception #unsupervisedlearning #selfsupervisedlearning #transferlearning

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Exciting news! CVGL got 6 papers accepted at ECCV, with an amazing unprecedented acceptance rate of ~85%!

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Hot new paper on 3D reconstruction by @NoSleepMusings @ChrisChoy208 @animesh_garg and team

Animesh Garg

@animesh_garg

7 years

Our new work on Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image aka DeformNet

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Congrats to all the authors

Fei-Fei Li

@drfeifei

6 years

Congratulations to Best Paper Award by @zamir_ar @silviocinguetta @StanfordCVGL & collaborators at #CVPR2018 , a computational map of perceptual task transfer learning!!

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

SegCloud was a recent Spotlight at 3DV and is the current leader on the reduced-8 benchmark.

Stanford Vision and Learning Lab

@StanfordSVL

7 years

Semantic Segmentation of 3D Point Clouds #3DV @lynetcha , @ChrisChoy208 Iro Armeni, @JunYoungGwak , @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

Humans have the remarkable ability to make and use tools to help them solve tasks. We introduce a framework for robots also to jointly learn to design and use tools via reinforcement learning. Poster: Thu 9th 2:45-3:30 pm Website:

Stephen Tian

@stephentian_

1 year

A robot may be unable to complete a task when limited by its morphology. Remarkably, people and some animals can get around this by not only using but also *designing* tools. We explore whether robots can also do this in our latest work! 🌐 🧵👇

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Lab PI @drfeifei wins the PAMI Longuest-Higgins Prize for the effort on ImageNet with @lijiali_vision @jiadeng @RichardSocher and team. Congrats everyone

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Discussing remarkable vision capacity of humans with roboticists at @IROS2017 #inspiration

Animesh Garg

@animesh_garg

7 years

Plenary by @drfeifei at @IROS2017 The Cambrian explosion in robots: Robots need eyes - Perception meets Robotics

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Come check out the poster on recent work in imitation learning at #NeurIPS

Animesh Garg

@animesh_garg

5 years

"AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers" Deep RL Workshop - Sat Dec 14 - Paper: @andrey_kurenkov @AjayMandlekar @RobobertoMM @silviocinguetta @StanfordSVL

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Three new papers from our lab to appear at #CoRL2017 @silviocinguetta @ozansener @NoSleepMusings @danfei_xu

Animesh Garg

@animesh_garg

7 years

Exciting lineup of accepted papers at #CoRL2017

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Students from the lab @RanjayKrishna and Apoorva Doradula describe their new work on engagement learning!

Stanford University

@Stanford

6 years

Ranjay Krishna and Apoorva Doradula use conversations as a strategy for training AI systems. They call it engagement learning – an AI “learns what kinds of concepts people like to discuss and how to ask questions to get an informative response.”

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

NOIR is a brain-robot interface that enables humans to command robots to perform 20 challenging everyday activities using their brain signals, such as cooking, cleaning, & playing games. Poster: Wed 8th 5:15pm Website:

Ruohan Zhang

@RuohanZhang76

1 year

Introducing our new work @corl_conf 2023, a novel brain-robot interface system: NOIR (Neural Signal Operated Intelligent Robots). Website: Paper: 🧠🤖

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Check out the workshop on a building causal models to go beyond reinforcement learning in robotics organized by lab members @animesh_garg and @yukez

Animesh Garg

@animesh_garg

6 years

Excited about the lineup of speakers to explore causality in robotics. RSS Workshop on Causal-Imitation. CfP is out and deadline for posters is Jun 3. Consider submitting! @yukez @ermonste @jiajunwu_cs and Michael Laskey

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

[2/2] 3. Regression Planning Networks. Xu et al. Congratulations to all the authors for their amazing work!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Exciting work on video analysis and another step on the path to having autonomous agents attempting to make us pasta

Animesh Garg

@animesh_garg

6 years

A great talk by Shyamal Buch at #CVPR18 on our paper on Weakly supervised reference aware visual grounding. @jcniebles @drfeifei @deanh619 Lucio Dery from @StanfordCVGL

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Fresh work from the lab!

Animesh Garg

@animesh_garg

7 years

Our new work on weakly supervised GANs for 3D shape from images Paper: Podcast:

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Stanford scientists are teaching a robot how not to be awkward in public via @qz

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

JR featuring at #NVIDIA GPU Tech Conference #GTC May 8-11 in Silicon Valley. Stop by!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

#Stanford 's #Jackrabbot is featured on NTY! @nytimes What Comes After the Roomba?

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

VoxPoser uses LLM+VLM to create 3D value maps in robot workspace, which guides motion planner to synthesize behaviors for everyday manipulation tasks w/o requiring robot data. Oral: Wed 8th 11:50 am Poster: Wed 8th 5:15-6:00 pm

Wenlong Huang

@wenlong_huang

1 year

How to harness foundation models for *generalization in the wild* in robot manipulation? Introducing VoxPoser: use LLM+VLM to label affordances and constraints directly in 3D perceptual space for zero-shot robot manipulation in the real world! 🌐 🧵👇

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

MimicPlay is an imitation learning algorithm that uses cheap human play data to unlock real-time planning for long-horizon manipulation. Oral: Thu 9th 8:30 am Poster: Thu 9th 2:45-3:30 pm Best paper/Best student paper finalist Best system paper finalist

Chen Wang

@chenwang_j

2 years

How to teach robots to perform long-horizon tasks efficiently and robustly🦾? Introducing MimicPlay - an imitation learning algorithm that uses "cheap human play data". Our approach unlocks both real-time planning through raw perception and strong robustness to disturbances!🧵👇

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Exciting direction of research by joint group, SVL, of @silviocinguetta and @drfeifei

Animesh Garg

@animesh_garg

7 years

Our new paper on Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Glad to share some of our efforts in healthcare

Stanford AI Lab

@StanfordAILab

6 years

Check out our first blog post about SAIL research, about how computer vision can be used to enable smart hospitals By Albert Haque & Michelle Guo ( @mshlguo ), led by professors Terry Platchek ( @TerryPlatchek ), Arnold Milstein, & Fei-Fei Li ( @drfeifei )

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

Sequential dexterity is a system that learns to chain multiple dexterous manipulation policies for tackling long-horizon manipulation tasks in both simulation and real-world. Poster: Tue 7th 2:45-3:30 pm

Chen Wang

@chenwang_j

1 year

How to chain multiple dexterous skills to tackle complex long-horizon manipulation tasks? Imagine retrieving a LEGO block from a pile, rotating it in-hand, and inserting it at the desired location to build a structure. Introducing our new work - Sequential Dexterity 🧵👇

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Lab PI @silviocinguetta meets up with dignitaries from the IT ministry of India to discuss AI challenges for India

Ravi Shankar Prasad

@rsprasad

6 years

It was an extra-ordinary visit to Stanford University. Had a wonderful exchange with its brilliant faculty on use of technology for human development and the application of AI and the challenge it poses. The faculty was deeply impressed with India's story of digital inclusion.

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Stanford Vision and Learning Lab

@StanfordSVL

10 years

Four papers have been accepted in CVPR 2015 including one oral presentation! Congratulations to all the authors!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Exciting work on one shot robot learning at #ICRA2018 @animesh_garg @yukez @danfei_xu @silviocinguetta @drfeifei

Animesh Garg

@animesh_garg

6 years

This is being presented at #ICRA2018 by @StanfordCVGL student @danfei_xu on Wed 05/23 in Brisbane. Come say hi if you attending -

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

A new effort from SVL and the JackRabbot team! New dataset and benchmark for robot perception in human environments. The winners of the first challenge on pedestrian detection and tracking will be presented at our workshop at #ICCV19 !

Roberto

@RobobertoMM

5 years

Want to see what JackRabbot sees? Finally a comprehensive dataset from the point of view of a mobile manipulating robot!

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

New study that analyzes different action spaces for RL in robot manipulation in the quest to find the best one. Guys what? The best method is a combination of operational space control (1986) with learned adaptive gain tuning. To appear at #IROS2019

Animesh Garg

@animesh_garg

5 years

What action space should we use for contact-rich manipulation? We show that Variable Impedance Control in End-Effector Space outperforms most other choices. Paper: w\ R. Martin-Martin, @michellearning , R. Gardner, @silviocinguetta , @leto__jean @StanfordSVL

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Stanford Vision and Learning Lab

@StanfordSVL

4 years

RL in multitask domains with shared underlying latent information can be made more effective through learning action space manifolds. Check out this effort on Learning latent Action Spaces at #ICRA2021

Animesh Garg

@animesh_garg

4 years

When you try to open a new door, do you try to yank it up? Likely, no. Why should your robot continue to do so! Check out our #ICRA2021 paper on learning action spaces for efficient contact-rich manipulation. paper:

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Stanford’s ‘Jackrabbot’ robot will attempt to learn the arcane and unspoken rules via @techcrunch

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Stanford Vision and Learning Lab

@StanfordSVL

9 years

Our paper "Robust Single-View Instance Recognition", by D. Held, S. Thrun , S. Savarese, has been accepted to ICRA

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Exciting new line of work from the group on 3D vision at #CVPR2019 by @lynetcha @SHamidRezatofig @silviocinguetta

Lyne Tchapmi

@lynetcha

5 years

Announcing the launch of "Completion3D: Stanford 3D Point Cloud Completion Benchmark” . Come check out our associated paper "TopNet: Structural Point Cloud Decoder" at #CVPR2019 ! @silviocinguetta @SHamidRezatofig @StanfordSVL

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Come check out labs new work at #ICRA2019 14:40-15:55, Grasping II 1.2.12 MoB1-12, Room 220 @silviocinguetta @ken_goldberg @animesh_garg @andrey_kurenkov

Animesh Garg

@animesh_garg

5 years

Presenting on Monday at #ICRA2019 Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter. w\ @ken_goldberg @andrey_kurenkov Paper: Video:

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Stanford Vision and Learning Lab

@StanfordSVL

1 year

Do you know how to make a dumpling🥟? Our robot🤖does! RoboCook is a robot system designed for long-horizon manipulation of elasto-plastic objects with a variety of tools. Oral: Tue 7th 8:50 am Poster: Tue 7th 2:45-3:30 pm Best system paper finalist

Haochen Shi

@HaochenShi74

1 year

Do you know how to make a dumpling🥟? Our robot🤖does! Introducing RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools. Project website: Here we show how RoboCook makes a dumpling under external human perturbation. Thread🧵👇

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Congrats @silviocinguetta . Looking forward to exciting research Stanford AI Center

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Our work on automated process for acquiring detailed building information featured in Stanford News via @Stanford

Stanford researchers automate process for acquiring detailed building information

Stanford computer scientists and civil engineers use computer vision to automate data collection for large renovation and remodeling projects.

news.stanford.edu

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

#3DV is sold out. Action packed schedule. See you all next week.

Ozan Sener

@ozansener

8 years

Vaoww!! #3DV is sold out, a great conference is waiting for all of us. See you all next Tuesday.

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

#3DV2016 Richard Szeliski Keynote on 3D Reconstruction for image based rendering

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Stanford Vision and Learning Lab

@StanfordSVL

5 years

Something all conferences should do

Animesh Garg

@animesh_garg

5 years

Robotics leading the way in inclusiveness by providing child care services at #ICRA2019

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

3DV program and tutorials are now online. Register now and mark your calenders for. Oct 25-28

Silvio Savarese

@silviocinguetta

8 years

The program for #3DV2016 is now available! Very exciting list of speakers, talks, demos, tutorials, and exhibitors!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

A very timely workshop on causality and robotics. Consider participating! Also see a recent piece on Judea Pearl's perspective on causality models in AI

Animesh Garg

@animesh_garg

6 years

Excited about the lineup of speakers to explore causality in robotics. RSS Workshop on Causal-Imitation. CfP is out and deadline for posters is Jun 3. Consider submitting! @yukez @ermonste @jiajunwu_cs and Michael Laskey

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Our work on deep Layout estimation have been picked up and featured on CVPR daily:

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

JackRabbot has been featured in the Stanford news:

Stanford's social robot 'Jackrabbot' seeks to understand pedestrian behavior

The Computational Vision and Geometry Lab has developed a robot prototype that could soon autonomously move among us, following normal human social etiquettes. It's named 'Jackrabbot' after the...

news.stanford.edu

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

Exiting workshop at #rss2018 from lab folks @animesh_garg and @yukez

Animesh Garg

@animesh_garg

6 years

Elias Boreinboim from Purdue explaining the causal heirarchy from Judea Pearl school of thought at workshop on causality and imitation #RSS2018

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

@ChrisChoy208 from CVGL presenting at #eccv2016 . Great Job Chris!

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Good news! We got two papers accepted to NIPS'16 (1 poster and 1 oral)

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Stanford’s ‘Jackrabbot’ paves way for social robotics via @Stanford_Daily

Stanford’s ‘Jackrabbot’ paves way for social robotics

Stanford researchers in the Computational Vision and Geometry Lab have designed an autonomously navigating robot prototype that they say understands implicit social conventions and human behavior.

stanforddaily.com

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Attending @cvpr2016 ? Vote for our 2019 CVPR Bid! More info at

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Stanford Vision and Learning Lab

@StanfordSVL

9 years

The #3dv2016 website is live!

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Our paper won the Google runner-up best paper award at the Vision from Satellite to Street 2015 Workshop!

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Stanford Vision and Learning Lab

@StanfordSVL

6 years

@leto__jean @animesh_garg @drfeifei @deanh619 @danfei_xu @yukez @jcniebles Thx @leto__jean

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

Congrats Ajay

Animesh Garg

@animesh_garg

7 years

Ajay Mandlekar from @StanfordCVGL gives a great talk at @IROS2017 @drfeifei @silviocinguetta

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

The deadline of early bird registration of 3DV 2016 is approaching (9/16). Do not forget to register here #3dv2016

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Stanford Vision and Learning Lab

@StanfordSVL

9 years

5 papers accepted to #cvpr2016 : 2 oral, 2 spotlight, 1 poster!

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

#3DV Program is online now. Exciting keynotes and talks starting next Tues 10/25

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Stanford team teaching robots manners via @abc7newsbayarea

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Stanford Vision and Learning Lab

@StanfordSVL

7 years

New work from our group on zero shot transfer in RL for Robotics

Animesh Garg

@animesh_garg

7 years

Our new work on Zero-shot transfer across stochastic dynamics

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

@silviocinguetta adding to the great conversation on ar/vr in vision at @ToyotaResearch workshop

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

We got the Stanford CIFE Seed Research Award to conduct research on parsing of buildings. See our latest work on it:

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

3DV 2016 is sold out. We look forward to seeing you all next Tuesday! #3dv2016

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

This Monday (10/17) we'll discuss building parsing, its potential and the AEC/FM industry at "The Modern Architect" radio show @KZSU 10-11AM

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Stanford Vision and Learning Lab

@StanfordSVL

6 months

Stanford SVL is a vibrant community of faculty, postdocs and students. Our alumni have landed in prestigious positions in academia and industry. We strive for an integrative and diverse group. We especially encourage applications from traditionally underrepresented groups in AI.

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

BBC News - Jackrabbot: Why this robot is watching how you move

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Stanford Vision and Learning Lab

@StanfordSVL

8 years

Exciting new datasets for progress in videos

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