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cs.CV2025
: A "Spot the Difference" Challenge for Large Multimodal Models
Kewei Wei, Bocheng Hu, Jie Cao +13
Modern Large Multimodal Models (LMMs) have demonstrated extraordinary ability in static image and single-state spatial-temporal understanding. However, their capacity to comprehend…
cs.CV2025
Frame-Difference Guided Dynamic Region Perception for CLIP Adaptation in Text-Video Retrieval
Jiaao Yu, Mingjie Han, Tao Gong +2
With the rapid growth of video data, text-video retrieval technology has become increasingly important in numerous application scenarios such as recommendation and search. Early te…
cs.CV2025
Noise is an Efficient Learner for Zero-Shot Vision-Language Models
Raza Imam, Asif Hanif, Jian Zhang +3
Recently, test-time adaptation has garnered attention as a method for tuning models without labeled data. The conventional modus operandi for adapting pre-trained vision-language m…