3 citations · 3 across the 6 of their papers we have counts for
6 papers
Weakly Supervised Incremental Segmentation via Semantic Anchors and Spatial Arbitration
Zhonggai Wang, Kai Fang, Guangyu Gao
Weakly Incremental Learning for Semantic Segmentation (WILSS) suffers from the continuous introduction of noisy supervision, which progressively corrupts class-level representation…
FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation
Zekang Zhang, Guangyu Gao, Youyun Tang +7
LLM-conditioned segmentation has recently advanced rapidly by coupling large language models with iterative mask generation frameworks. However, we identify a persistent failure mo…
Rethinking MLLM Itself as a Segmenter with a Single Segmentation Token
Anqi Zhang, Xiaokang Ji, Guangyu Gao +3
Recent segmentation methods leveraging Multi-modal Large Language Models (MLLMs) have shown reliable object-level segmentation and enhanced spatial perception. However, almost all…
CoMBO: Conflict Mitigation via Branched Optimization for Class Incremental Segmentation
Kai Fang, Anqi Zhang, Guangyu Gao +3
Effective Class Incremental Segmentation (CIS) requires simultaneously mitigating catastrophic forgetting and ensuring sufficient plasticity to integrate new classes. The inherent…
Bridge the Points: Graph-based Few-shot Segment Anything Semantically
Anqi Zhang, Guangyu Gao, Jianbo Jiao +2
The recent advancements in large-scale pre-training techniques have significantly enhanced the capabilities of vision foundation models, notably the Segment Anything Model (SAM), w…
CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation
Zekang Zhang, Guangyu Gao, Jianbo Jiao +2
Class incremental semantic segmentation aims to strike a balance between the model's stability and plasticity by maintaining old knowledge while adapting to new concepts. However,…