Jitendra Malik

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berkeley college

Professor of EECS University of California at Berkeley

Distribution-Free, Risk-Controlling Prediction Sets

To communicate instance-wise uncertainty for prediction tasks, we show h...
01/07/2021 ∙ by Stephen Bates, et al. ∙ 11 ∙ share

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Reconstructing Hand-Object Interactions in the Wild

In this work we explore reconstructing hand-object interactions in the w...
12/17/2020 ∙ by Zhe Cao, et al. ∙ 2 ∙ share

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Human Mesh Recovery from Multiple Shots

Videos from edited media like movies are a useful, yet under-explored so...
12/17/2020 ∙ by Georgios Pavlakos, et al. ∙ 2 ∙ share

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From Goals, Waypoints Paths To Long Term Human Trajectory Forecasting

Human trajectory forecasting is an inherently multi-modal problem. Uncer...
12/02/2020 ∙ by Karttikeya Mangalam, et al. ∙ 16 ∙ share

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Better Knowledge Retention through Metric Learning

In continual learning, new categories may be introduced over time, and a...
11/26/2020 ∙ by Ke Li, et al. ∙ 4 ∙ share

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Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation

Vision-based robotics often separates the control loop into one module f...
11/13/2020 ∙ by Bryan Chen, et al. ∙ 0 ∙ share

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Rearrangement: A Challenge for Embodied AI

We describe a framework for research and evaluation in Embodied AI. Our ...
11/03/2020 ∙ by Dhruv Batra, et al. ∙ 2 ∙ share

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Shape, Illumination, and Reflectance from Shading

A fundamental problem in computer vision is that of inferring the intrin...
10/07/2020 ∙ by Jonathan T. Barron, et al. ∙ 0 ∙ share

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Uncertainty Sets for Image Classifiers using Conformal Prediction

Convolutional image classifiers can achieve high predictive accuracy, bu...
09/29/2020 ∙ by Anastasios Angelopoulos, et al. ∙ 8 ∙ share

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Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

Learning long-term dynamics models is the key to understanding physical ...
08/05/2020 ∙ by Haozhi Qi, et al. ∙ 2 ∙ share

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Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild

We present a method that infers spatial arrangements and shapes of human...
07/30/2020 ∙ by Jason Y. Zhang, et al. ∙ 12 ∙ share

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Shape and Viewpoint without Keypoints

We present a learning framework that learns to recover the 3D shape, pos...
07/21/2020 ∙ by Shubham Goel, et al. ∙ 2 ∙ share

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3D Shape Reconstruction from Vision and Touch

When a toddler is presented a new toy, their instinctual behaviour is to...
07/07/2020 ∙ by Edward J. Smith, et al. ∙ 7 ∙ share

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Long-term Human Motion Prediction with Scene Context

Human movement is goal-directed and influenced by the spatial layout of ...
07/07/2020 ∙ by Zhe Cao, et al. ∙ 6 ∙ share

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Deep Isometric Learning for Visual Recognition

Initialization, normalization, and skip connections are believed to be t...
06/30/2020 ∙ by Haozhi Qi, et al. ∙ 15 ∙ share

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Robust Learning Through Cross-Task Consistency

Visual perception entails solving a wide set of tasks, e.g., object dete...
06/07/2020 ∙ by Amir Zamir, et al. ∙ 12 ∙ share

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State-Only Imitation Learning for Dexterous Manipulation

Dexterous manipulation has been a long-standing challenge in robotics. R...
04/07/2020 ∙ by Ilija Radosavovic, et al. ∙ 1 ∙ share

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Inclusive GAN: Improving Data and Minority Coverage in Generative Models

Generative Adversarial Networks (GANs) have brought about rapid progress...
04/07/2020 ∙ by Ning Yu, et al. ∙ 5 ∙ share

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Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation

Many tasks in computer vision and graphics fall within the framework of ...
04/07/2020 ∙ by Ke Li, et al. ∙ 7 ∙ share

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Audiovisual SlowFast Networks for Video Recognition

We present Audiovisual SlowFast Networks, an architecture for integrated...
01/23/2020 ∙ by Fanyi Xiao, et al. ∙ 23 ∙ share

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Side-Tuning: Network Adaptation via Additive Side Networks

When training a neural network for a desired task, one may prefer to ada...
12/31/2019 ∙ by Jeffrey O Zhang, et al. ∙ 15 ∙ share

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Learning to Navigate Using Mid-Level Visual Priors

How much does having visual priors about the world (e.g. the fact that t...
12/23/2019 ∙ by Alexander Sax, et al. ∙ 6 ∙ share

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3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera

A comprehensive semantic understanding of a scene is important for many ...
10/06/2019 ∙ by Iro Armeni, et al. ∙ 28 ∙ share

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Predicting 3D Human Dynamics from Video

Given a video of a person in action, we can easily guess the 3D future m...
08/13/2019 ∙ by Jason Y. Zhang, et al. ∙ 15 ∙ share

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Learning Individual Styles of Conversational Gesture

Human speech is often accompanied by hand and arm gestures. Given audio ...
06/10/2019 ∙ by Shiry Ginosar, et al. ∙ 11 ∙ share

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Mesh R-CNN

Rapid advances in 2D perception have led to systems that accurately dete...
06/06/2019 ∙ by Georgia Gkioxari, et al. ∙ 5 ∙ share

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Learning Navigation Subroutines by Watching Videos

Hierarchies are an effective way to boost sample efficiency in reinforce...
05/29/2019 ∙ by Ashish Kumar, et al. ∙ 9 ∙ share

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Which Tasks Should Be Learned Together in Multi-task Learning?

Many computer vision applications require solving multiple tasks in real...
05/18/2019 ∙ by Trevor Standley, et al. ∙ 0 ∙ share

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ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors

Instance segmentation aims to detect and segment individual objects in a...
04/05/2019 ∙ by Weicheng Kuo, et al. ∙ 8 ∙ share

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Habitat: A Platform for Embodied AI Research

We present Habitat, a new platform for research in embodied artificial i...
04/02/2019 ∙ by Manolis Savva, et al. ∙ 58 ∙ share

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Combining Optimal Control and Learning for Visual Navigation in Novel Environments

Model-based control is a popular paradigm for robot navigation because i...
03/06/2019 ∙ by Somil Bansal, et al. ∙ 10 ∙ share

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Trajectory Normalized Gradients for Distributed Optimization

Recently, researchers proposed various low-precision gradient compressio...
01/24/2019 ∙ by Jianqiao Wangni, et al. ∙ 14 ∙ share

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Learning Independent Object Motion from Unlabelled Stereoscopic Videos

We present a system for learning motion of independently moving objects ...
01/07/2019 ∙ by Zhe Cao, et al. ∙ 16 ∙ share

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Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Active Tasks

One of the ultimate promises of computer vision is to help robotic agent...
12/31/2018 ∙ by Alexander Sax, et al. ∙ 8 ∙ share

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Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors

Unconditional image generation has recently been dominated by generative...
12/21/2018 ∙ by Yedid Hoshen, et al. ∙ 28 ∙ share

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SlowFast Networks for Video Recognition

We present SlowFast networks for video recognition. Our model involves (...
12/10/2018 ∙ by Christoph Feichtenhofer, et al. ∙ 0 ∙ share

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Learning 3D Human Dynamics from Video

From an image of a person in action, we can easily guess the 3D motion o...
12/04/2018 ∙ by Angjoo Kanazawa, et al. ∙ 0 ∙ share

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Visual Memory for Robust Path Following

Humans routinely retrace paths in a novel environment both forwards and ...
12/03/2018 ∙ by Ashish Kumar, et al. ∙ 0 ∙ share

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Are All Training Examples Created Equal? An Empirical Study

Modern computer vision algorithms often rely on very large training data...
11/30/2018 ∙ by Kailas Vodrahalli, et al. ∙ 0 ∙ share

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On the Implicit Assumptions of GANs

Generative adversarial nets (GANs) have generated a lot of excitement. D...
11/29/2018 ∙ by Ke Li, et al. ∙ 0 ∙ share

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Diverse Image Synthesis from Semantic Layouts via Conditional IMLE

Most existing methods for conditional image synthesis are only able to g...
11/29/2018 ∙ by Ke Li, et al. ∙ 16 ∙ share

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SFV: Reinforcement Learning of Physical Skills from Videos

Data-driven character animation based on motion capture can produce high...
10/08/2018 ∙ by Xue Bin Peng, et al. ∙ 8 ∙ share

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Super-Resolution via Conditional Implicit Maximum Likelihood Estimation

Single-image super-resolution (SISR) is a canonical problem with diverse...
10/02/2018 ∙ by Ke Li, et al. ∙ 0 ∙ share

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Implicit Maximum Likelihood Estimation

Implicit probabilistic models are models defined naturally in terms of a...
09/24/2018 ∙ by Ke Li, et al. ∙ 20 ∙ share

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Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection

Deep learning for clinical applications is subject to stringent performa...
09/08/2018 ∙ by Weicheng Kuo, et al. ∙ 0 ∙ share

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Gibson Env: Real-World Perception for Embodied Agents

Developing visual perception models for active agents and sensorimotor c...
08/31/2018 ∙ by Fei Xia, et al. ∙ 6 ∙ share

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On Evaluation of Embodied Navigation Agents

Skillful mobile operation in three-dimensional environments is a primary...
07/18/2018 ∙ by Peter Anderson, et al. ∙ 0 ∙ share

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Learning Instance Segmentation by Interaction

We present an approach for building an active agent that learns to segme...
06/21/2018 ∙ by Deepak Pathak, et al. ∙ 2 ∙ share

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PatchFCN for Intracranial Hemorrhage Detection

This paper studies the problem of detecting acute intracranial hemorrhag...
06/08/2018 ∙ by Weicheng Kuo, et al. ∙ 2 ∙ share

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More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch

For humans, the process of grasping an object relies heavily on rich tac...
05/28/2018 ∙ by Roberto Calandra, et al. ∙ 6 ∙ share

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Jitendra Malik

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