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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…
GREx: Generalized Referring Expression Segmentation, Comprehension, and Generation
Henghui Ding, Chang Liu, Shuting He +2
Referring Expression Segmentation (RES) and Comprehension (REC) respectively segment and detect the object described by an expression, while Referring Expression Generation (REG) g…
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…
Open-set Anomaly Segmentation in Complex Scenarios
Song Xia, Yi Yu, Henghui Ding +4
Precise segmentation of out-of-distribution (OoD) objects, herein referred to as anomalies, is crucial for the reliable deployment of semantic segmentation models in open-set, safe…
Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension
Yaxian Wang, Henghui Ding, Shuting He +3
In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuse…
SegPoint: Segment Any Point Cloud via Large Language Model
Shuting He, Henghui Ding, Xudong Jiang +1
Despite significant progress in 3D point cloud segmentation, existing methods primarily address specific tasks and depend on explicit instructions to identify targets, lacking the…
Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing
Song Xia, Yi Yu, Xudong Jiang +1
Randomized Smoothing (RS) has been proven a promising method for endowing an arbitrary image classifier with certified robustness. However, the substantial uncertainty inherent in…