656 citations · 1.1k across the 55 of their papers we have counts for
9 papers · 1 filter
V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects
Xingyu Liu, Kris M. Kitani
Manipulating articulated objects requires multiple robot arms in general. It is challenging to enable multiple robot arms to collaboratively complete manipulation tasks on articula…
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
Khoa Vo, Hyekang Joo, Kashu Yamazaki +4
Humans typically perceive the establishment of an action in a video through the interaction between an actor and the surrounding environment. An action only starts when the main ac…
Sequential Voting with Relational Box Fields for Active Object Detection
Qichen Fu, Xingyu Liu, Kris M. Kitani
A key component of understanding hand-object interactions is the ability to identify the active object -- the object that is being manipulated by the human hand. In order to accura…
Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Ye Yuan, Yuda Song, Zhengyi Luo +2
An agent's functionality is largely determined by its design, i.e., skeletal structure and joint attributes (e.g., length, size, strength). However, finding the optimal agent desig…
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present KDFNet, a novel method for 6D object pose estimation from RGB images. To handle occlusion, many recent works have proposed to localize 2D keypoints through pixel-wise vo…
StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present a large-scale stereo RGB image object pose estimation dataset named the dataset. The dataset is designed to address challenging cases such as obje…
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
S. Alireza Golestaneh, Saba Dadsetan, Kris M. Kitani
The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the perceptual image quality in accordance with subjective evaluations, it is a complex and unsolved probl…
Neighborhood-Aware Neural Architecture Search
Xiaofang Wang, Shengcao Cao, Mengtian Li +1
Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting. To achieve better generaliza…
RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering
Shun Iwase, Xingyu Liu, Rawal Khirodkar +2
We present RePOSE, a fast iterative refinement method for 6D object pose estimation. Prior methods perform refinement by feeding zoomed-in input and rendered RGB images into a CNN…