6 papers
SeGPruner: Semantic-Geometric Visual Token Pruner for 3D Question Answering
Wenli Li, Kai Zhao, Haoran Jiang +3
Vision-language models (VLMs) have been widely adopted for 3D question answering (3D QA). In typical pipelines, visual tokens extracted from multiple viewpoints are concatenated wi…
Heuristic Self-Paced Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions
Shiqin Wang, Haoyang Chen, Huaizhou Huang +6
The learning order of semantic classes significantly impacts unsupervised domain adaptation for semantic segmentation, especially under adverse weather conditions. Most existing cu…
InstanceRSR: Real-World Super-Resolution via Instance-Aware Representation Alignment
Zixin Guo, Kai Zhao, Luyan Zhang
Existing real-world super-resolution (RSR) methods based on generative priors have achieved remarkable progress in producing high-quality and globally consistent reconstructions. H…
Open-Vocabulary Camouflaged Object Segmentation with Cascaded Vision Language Models
Kai Zhao, Wubang Yuan, Zheng Wang +4
Open-Vocabulary Camouflaged Object Segmentation (OVCOS) seeks to segment and classify camouflaged objects from arbitrary categories, presenting unique challenges due to visual ambi…
Attention Debiasing for Token Pruning in Vision Language Models
Kai Zhao, Wubang Yuan, Yuchen Lin +5
Vision-language models (VLMs) typically encode substantially more visual tokens than text tokens, resulting in significant token redundancy. Pruning uninformative visual tokens is…
Vision-Motion-Reference Alignment for Referring Multi-Object Tracking via Multi-Modal Large Language Models
Weiyi Lv, Ning Zhang, Hanyang Sun +4
Referring Multi-Object Tracking (RMOT) extends conventional multi-object tracking (MOT) by introducing natural language references for multi-modal fusion tracking. RMOT benchmarks…