4 papers
ScaleHP: Scale-Mediated Optimization of Coupled Errors for Metric-Space Hand Pose Estimation
Ruitao Jing, Xingyu Chen, Hongyang Li +3
In this paper, we present ScaleHP, a unified framework that explicitly represents per-instance metric scale to resolve the coupled errors in calibrated camera-space hand pose estim…
SegDINO3D: 3D Instance Segmentation Empowered by Both Image-Level and Object-Level 2D Features
Jinyuan Qu, Hongyang Li, Xingyu Chen +5
In this paper, we present SegDINO3D, a novel Transformer encoder-decoder framework for 3D instance segmentation. As 3D training data is generally not as sufficient as 2D training i…
TAPTRv3: Spatial and Temporal Context Foster Robust Tracking of Any Point in Long Video
Jinyuan Qu, Hongyang Li, Shilong Liu +3
In this paper, built upon TAPTRv2, we present TAPTRv3. TAPTRv2 is a simple yet effective DETR-like point tracking framework that works fine in regular videos but tends to fail in l…
TAPTRv2: Attention-based Position Update Improves Tracking Any Point
Hongyang Li, Hao Zhang, Shilong Liu +5
In this paper, we present TAPTRv2, a Transformer-based approach built upon TAPTR for solving the Tracking Any Point (TAP) task. TAPTR borrows designs from DEtection TRansformer (DE…