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20242026
most citedEvaluating SAM2 for Video Semantic Segmentation

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

cs.LG2026

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…

cs.CV20251 cited

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…

cs.CV2025

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…

eess.IV2025

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…

cs.CV2025

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-…

cs.CV2025

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…