23 citations · 32 across the 9 of their papers we have counts for
9 papers
AgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos
Kirill Mazur, Nikita Karaev, Matthew Chang +2
In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first estimate dense pixel correspo…
Diffusion Meets DAgger: Supercharging Eye-in-hand Imitation Learning
Xiaoyu Zhang, Matthew Chang, Pranav Kumar +1
A common failure mode for policies trained with imitation is compounding execution errors at test time. When the learned policy encounters states that are not present in the expert…
3D Hand Pose Estimation in Everyday Egocentric Images
Aditya Prakash, Ruisen Tu, Matthew Chang +1
3D hand pose estimation in everyday egocentric images is challenging for several reasons: poor visual signal (occlusion from the object of interaction, low resolution & motion blur…
GOAT: GO to Any Thing
Matthew Chang, Theophile Gervet, Mukul Khanna +10
In deployment scenarios such as homes and warehouses, mobile robots are expected to autonomously navigate for extended periods, seamlessly executing tasks articulated in terms that…
Look Ma, No Hands! Agent-Environment Factorization of Egocentric Videos
Matthew Chang, Aditya Prakash, Saurabh Gupta
The analysis and use of egocentric videos for robotic tasks is made challenging by occlusion due to the hand and the visual mismatch between the human hand and a robot end-effector…
3D Reconstruction of Objects in Hands without Real World 3D Supervision
Aditya Prakash, Matthew Chang, Matthew Jin +2
Prior works for reconstructing hand-held objects from a single image train models on images paired with 3D shapes. Such data is challenging to gather in the real world at scale. Co…
One-shot Visual Imitation via Attributed Waypoints and Demonstration Augmentation
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. In this setting, an agent must solve a novel in…
Learning Value Functions from Undirected State-only Experience
Matthew Chang, Arjun Gupta, Saurabh Gupta
This paper tackles the problem of learning value functions from undirected state-only experience (state transitions without action labels i.e. (s,s',r) tuples). We first theoretica…
Semantic Visual Navigation by Watching YouTube Videos
Matthew Chang, Arjun Gupta, Saurabh Gupta
Semantic cues and statistical regularities in real-world environment layouts can improve efficiency for navigation in novel environments. This paper learns and leverages such seman…