Search Results for author: Matthew Chang

Found 7 papers, 1 papers with code

GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation

no code implementations9 Apr 2024 Mukul Khanna, Ram Ramrakhya, Gunjan Chhablani, Sriram Yenamandra, Theophile Gervet, Matthew Chang, Zsolt Kira, Devendra Singh Chaplot, Dhruv Batra, Roozbeh Mottaghi

The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images.

Navigate Visual Navigation

Diffusion Meets DAgger: Supercharging Eye-in-hand Imitation Learning

no code implementations27 Feb 2024 XiaoYu Zhang, Matthew Chang, Pranav Kumar, Saurabh Gupta

The Dataset Aggregation, or DAgger approach to this problem simply collects more data to cover these failure states.

Imitation Learning

3D Hand Pose Estimation in Egocentric Images in the Wild

no code implementations11 Dec 2023 Aditya Prakash, Ruisen Tu, Matthew Chang, Saurabh Gupta

We present WildHands, a method for 3D hand pose estimation in egocentric images in the wild.

3D Hand Pose Estimation

Learning Hand-Held Object Reconstruction from In-The-Wild Videos

no code implementations4 May 2023 Aditya Prakash, Matthew Chang, Matthew Jin, Saurabh Gupta

Prior works for reconstructing hand-held objects from a single image rely on direct 3D shape supervision which is challenging to gather in real world at scale.

Object Object Reconstruction

One-shot Visual Imitation via Attributed Waypoints and Demonstration Augmentation

no code implementations9 Feb 2023 Matthew Chang, Saurabh Gupta

In this paper, we analyze the behavior of existing techniques and design new solutions for the problem of one-shot visual imitation.

Data Augmentation

Learning Value Functions from Undirected State-only Experience

no code implementations ICLR 2022 Matthew Chang, Arjun Gupta, Saurabh Gupta

We show that LAQ can recover value functions that have high correlation with value functions learned using ground truth actions.

Future prediction Imitation Learning +3

Semantic Visual Navigation by Watching YouTube Videos

1 code implementation NeurIPS 2020 Matthew Chang, Arjun Gupta, Saurabh Gupta

Semantic cues and statistical regularities in real-world environment layouts can improve efficiency for navigation in novel environments.

Q-Learning Visual Navigation

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