1 citations · 2 across the 15 of their papers we have counts for
17 papers
STAC: Selective Spatiotemporal Aggregation and Compression for Video Reasoning Segmentation
Syed Ariff Syed Hesham, Yun Liu, Guolei Sun +4
Video reasoning segmentation demands pixel-accurate object tracking across hundreds of frames under complex natural language queries, producing dense spatiotemporal tokens whose qu…
DCP-Prune: Ultra-Low Token Pruning with Distribution Consistency Preservation
Xifeng Xue, Xiaokang Wang, Zirui Li +2
Recent vision token pruning methods effectively preserve model performance under moderate token budgets but become unstable under ultra-low token budget. Our analysis shows that as…
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
Yi Zhong, Haotong Qin, Xindong Zhang +2
Low-bit post-training quantization (PTQ) is a pivotal technique for deploying Vision-Language Models (VLMs) on resource-constrained devices. However, existing PTQ methods often deg…
DINO-Mix: Distilling Foundational Knowledge with Cross-Domain CutMix for Semi-supervised Class-imbalanced Medical Image Segmentation
Xinyu Liu, Guolei Sun
Semi-supervised learning (SSL) has emerged as a critical paradigm for medical image segmentation, mitigating the immense cost of dense annotations. However, prevailing SSL framewor…
Revisiting Adaptive Rounding with Vectorized Reparameterization for LLM Quantization
Yuli Zhou, Qingxuan Chen, Luca Benini +2
Adaptive Rounding has emerged as an alternative to round-to-nearest (RTN) for post-training quantization by enabling cross-element error cancellation. Yet, dense and element-wise r…
EgoSound: Benchmarking Sound Understanding in Egocentric Videos
Bingwen Zhu, Yuqian Fu, Qiaole Dong +6
Multimodal Large Language Models (MLLMs) have recently achieved remarkable progress in vision-language understanding. Yet, human perception is inherently multisensory, integrating…
Evaluating SAM2 for Video Semantic Segmentation
Syed Hesham Syed Ariff, Yun Liu, Guolei Sun +4
The Segmentation Anything Model 2 (SAM2) has proven to be a powerful foundation model for promptable visual object segmentation in both images and videos, capable of storing object…
MedVSR: Medical Video Super-Resolution with Cross State-Space Propagation
Xinyu Liu, Guolei Sun, Cheng Wang +2
High-resolution (HR) medical videos are vital for accurate diagnosis, yet are hard to acquire due to hardware limitations and physiological constraints. Clinically, the collected l…
HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking
Ruixiang Chen, Guolei Sun, Yawei Li +2
This paper presents enhancements to the SAM2 framework for video object tracking task, addressing challenges such as occlusions, background clutter, and target reappearance. We int…
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
Guohuan Xie, Syed Ariff Syed Hesham, Wenya Guo +4
Video Scene Parsing (VSP) studies dense video understanding, where every pixel in each frame must be segmented, each region must be named, and each object identity must remain cohe…
Exploiting Temporal State Space Sharing for Video Semantic Segmentation
Syed Ariff Syed Hesham, Yun Liu, Guolei Sun +5
Video semantic segmentation (VSS) plays a vital role in understanding the temporal evolution of scenes. Traditional methods often segment videos frame-by-frame or in a short tempor…
CamSAM2: Segment Anything Accurately in Camouflaged Videos
Yuli Zhou, Yawei Li, Yuqian Fu +3
Video camouflaged object segmentation (VCOS), aiming at segmenting camouflaged objects that seamlessly blend into their environment, is a fundamental vision task with various real-…
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model
Zhaochong An, Guolei Sun, Yun Liu +4
Generalized few-shot 3D point cloud segmentation (GFS-PCS) adapts models to new classes with few support samples while retaining base class segmentation. Existing GFS-PCS methods e…
SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation
Shi-Feng Peng, Guolei Sun, Yong Li +2
The primary challenge of cross-domain few-shot segmentation (CD-FSS) is the domain disparity between the training and inference phases, which can exist in either the input data or…
Towards Open-Vocabulary Video Semantic Segmentation
Xinhao Li, Yun Liu, Guolei Sun +3
Semantic segmentation in videos has been a focal point of recent research. However, existing models encounter challenges when faced with unfamiliar categories. To address this, we…
Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu +5
Few-shot 3D point cloud segmentation (FS-PCS) aims at generalizing models to segment novel categories with minimal annotated support samples. While existing FS-PCS methods have sho…
When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptation
Yuli Zhou, Guolei Sun, Yawei Li +3
This study investigates the application and performance of the Segment Anything Model 2 (SAM2) in the challenging task of video camouflaged object segmentation (VCOS). VCOS involve…