9 citations · 11 across the 7 of their papers we have counts for
7 papers
DeCO: Discriminative Evidence Composition for Fine-Grained Dataset Distillation
Chuixuan Fan, Guang Li, Shijie Wang +5
Dataset distillation compresses a large training set into a compact synthetic set while preserving its downstream utility. However, existing methods primarily preserve global image…
LabRobFail: A Benchmark for Robotic Failure Analysis in Chemical Self-driving Laboratory
Haobo Wang, Baoli Sun, Anqi Zou +8
The deployment of embodied agents in self-driving laboratories could accelerate scientific discovery, yet their reliability is constrained by the irreversible and safety-critical n…
FD: A Dedicated Framework for Fine-Grained Dataset Distillation
Hongxu Ma, Guang Li, Shijie Wang +5
Dataset distillation (DD) compresses a large training set into a small synthetic set, reducing storage and training cost, and has shown strong results on general benchmarks. Decoup…
Towards an Effective Action-Region Tracking Framework for Fine-grained Video Action Recognition
Baoli Sun, Yihan Wang, Xinzhu Ma +3
Fine-grained action recognition (FGAR) aims to identify subtle and distinctive differences among fine-grained action categories. However, current recognition methods often capture…
Referring Video Object Segmentation with Cross-Modality Proxy Queries
Baoli Sun, Xinzhu Ma, Ning Wang +2
Referring video object segmentation (RVOS) is an emerging cross-modality task that aims to generate pixel-level maps of the target objects referred by given textual expressions. Th…
Semantic decomposition Network with Contrastive and Structural Constraints for Dental Plaque Segmentation
Jian Shi, Baoli Sun, Xinchen Ye +5
Segmenting dental plaque from images of medical reagent staining provides valuable information for diagnosis and the determination of follow-up treatment plan. However, accurate de…
Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution
Baoli Sun, Xinchen Ye, Baopu Li +3
Existing color-guided depth super-resolution (DSR) approaches require paired RGB-D data as training samples where the RGB image is used as structural guidance to recover the degrad…