147 citations · 337 across the 23 of their papers we have counts for
6 papers · 1 filter
Towards Omni-supervised Referring Expression Segmentation
Minglang Huang, Yiyi Zhou, Gen Luo +3
Referring Expression Segmentation (RES) is an emerging task in computer vision, which segments the target instances in images based on text descriptions. However, its development i…
3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation
Changli Wu, Yiwei Ma, Qi Chen +4
In 3D Referring Expression Segmentation (3D-RES), the earlier approach adopts a two-stage paradigm, extracting segmentation proposals and then matching them with referring expressi…
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Gen Luo, Yiyi Zhou, Tianhe Ren +3
Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the ne…
Towards Efficient Visual Adaption via Structural Re-parameterization
Gen Luo, Minglang Huang, Yiyi Zhou +4
Parameter-efficient transfer learning (PETL) is an emerging research spot aimed at inexpensively adapting large-scale pre-trained models to downstream tasks. Recent advances have a…
Active Teacher for Semi-Supervised Object Detection
Peng Mi, Jianghang Lin, Yiyi Zhou +7
In this paper, we study teacher-student learning from the perspective of data initialization and propose a novel algorithm called Active Teacher(Source code are available at: \url{…
Towards End-to-end Semi-supervised Learning for One-stage Object Detection
Gen Luo, Yiyi Zhou, Lei Jin +2
Semi-supervised object detection (SSOD) is a research hot spot in computer vision, which can greatly reduce the requirement for expensive bounding-box annotations. Despite great su…