10 citations · 29 across the 11 of their papers we have counts for
7 papers · 1 filter
Deformer: Dynamic Fusion Transformer for Robust Hand Pose Estimation
Qichen Fu, Xingyu Liu, Ran Xu +2
Accurately estimating 3D hand pose is crucial for understanding how humans interact with the world. Despite remarkable progress, existing methods often struggle to generate plausib…
Tripartite: Tackle Noisy Labels by a More Precise Partition
Xuefeng Liang, Longshan Yao, Xingyu Liu +1
Samples in large-scale datasets may be mislabeled due to various reasons, and Deep Neural Networks can easily over-fit to the noisy label data. To tackle this problem, the key poin…
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…
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Kristen Grauman, Andrew Westbury, Eugene Byrne +82
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outd…
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…
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…