7 papers · 1 filter
Action-Geometry Prediction with 3D Geometric Prior for Bimanual Manipulation
Chongyang Xu, Haipeng Li, Shen Cheng +4
Bimanual manipulation requires policies that can reason about 3D geometry, anticipate how it evolves under action, and generate smooth, coordinated motions. However, existing metho…
HeRO: Hierarchical 3D Semantic Representation for Pose-aware Object Manipulation
Chongyang Xu, Shen Cheng, Haipeng Li +3
Imitation learning for robotic manipulation has progressed from 2D image policies to 3D representations that explicitly encode geometry. Yet purely geometric policies often lack ex…
You Only Look Around: Learning Illumination Invariant Feature for Low-light Object Detection
Mingbo Hong, Shen Cheng, Haibin Huang +2
In this paper, we introduce YOLA, a novel framework for object detection in low-light scenarios. Unlike previous works, we propose to tackle this challenging problem from the persp…
Neural Spectral Decomposition for Dataset Distillation
Shaolei Yang, Shen Cheng, Mingbo Hong +3
In this paper, we propose Neural Spectrum Decomposition, a generic decomposition framework for dataset distillation. Unlike previous methods, we consider the entire dataset as a hi…
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
Yawei Li, Kai Zhang, Radu Timofte +108
This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment
Ziwei Luo, Youwei Li, Shen Cheng +6
This work addresses the Burst Super-Resolution (BurstSR) task using a new architecture, which requires restoring a high-quality image from a sequence of noisy, misaligned, and low-…