activity
20242026
collaborators

16 papers

cs.CV2026

Memory-Supported Synergistic Adaptation for Training-Free Test-Time Medical Image Segmentation

Lingrui Li, Nan Pu, Dong Zhao +4

Test-time adaptation (TTA) aims to mitigate distribution shifts by adapting models with unlabeled target data at inference time. While TTA with vision-language models (VLMs) has sh…

cs.CV2026

Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding

Boyan Wang, Yongxi Huang, Wenjing Li +4

This report presents our solution for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge, which requires parsing unstructured outdoor scenes from four camera platf…

cs.AI2026

CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection

Jinjie Shen, Yaxiong Wang, Yujiao Wu +5

The rapid rise of generative AI has made multimodal fake news increasingly realistic and pervasive, posing severe threats to public trust and social stability. Existing detection m…

cs.CV2026

OmniVL-Guard Pro: A Tool-Augmented Agent for Omnibus Vision-Language Forensics

Jinjie Shen, Zheng Huang, Yuchen Zhang +7

Existing vision-language forgery detection and grounding methods operate under a closed-world paradigm, assuming verification can be completed by the model alone. However, self-con…

cs.CV2026

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

Jinjie Shen, Jing Wu, Yaxiong Wang +5

Existing forgery detection methods are often limited to uni-modal or bi-modal settings, failing to handle the interleaved text, images, and videos prevalent in real-world misinform…

cs.LG2026

The Devil Is in Gradient Entanglement: Energy-Aware Gradient Coordinator for Robust Generalized Category Discovery

Haiyang Zheng, Nan Pu, Yaqi Cai +4

Generalized Category Discovery (GCD) leverages labeled data to categorize unlabeled samples from known or unknown classes. Most previous methods jointly optimize supervised and uns…