10 accepted papers
Federated Prompt Learning (FPL) has recently attracted increasing attention for its ability to leverage large-scale vision-language models such as CLIP within federated learning frameworks. While existing studies have advanced FPL through personalization strategies to enhance client-specific perform
Cross-view geo-localization is a critical task for UAV navigation, event detection, and aerial surveying, which establish correspondence between drone-captured and satellite imagery. Most existing approaches embed cross-view data into a joint feature space to maximize similarity between paired image
In real-world applications, video action recognition models must continuously learn new action categories while retaining previously acquired knowledge. However, most existing approaches rely on storing historical data for replay, which introduces storage burdens and raises data privacy concerns. To
Skill-based agent systems tackle complex tasks by composing reusable skills, improving modularity and scalability while introducing a largely unexamined security attack surface. We propose \textbf{SkillTrojan}, a backdoor attack that targets skill implementations rather than model parameters or trai…
State-of-the-art vision-language models (VLMs) require massive scaling that limits practical deployment. Small-scale VLMs offer a practical alternative but face out-of-domain (OOD) collapse when trained with traditional supervised fine-tuning (SFT). Through GeneralPoints experiments, we identify tha
Existing continual deepfake detection methods typically treat stability (retaining previously learned forgery knowl- edge) and plasticity (adapting to novel forgeries) as con- flicting properties, emphasizing an inherent trade-off be- tween them, while regarding generalization to unseen forg- eries…
Adversarial Robust Distillation (ARD) has emerged as a potent defense mechanism tailored to small models against adversarial threats. However, mainstream ARD methods typically exploit teachers’ response as the transferred knowledge, while neglecting the analysis of involved target-related knowledge…
Lip reading aims at transforming the videos of continuous lip movement into textual contents, and has achieved significant progress over the past decade. It serves as a critical yet practical assistance for speech-impaired individuals, with more practicability than speech recognition in noisy enviro…
Current VQA models are suffering from the problem of overdependence on language bias, which severely reduces their robustness in real-world scenarios. In this paper, we analyze VQA models from the view of forward/backward chaining in the inference engine, and propose to enhance their robustness via…
A major challenge in matching between vision and language is that they typically have completely different features and representations. In this work, we introduce a novel bridge between the modality-specific representations by creating a co-embedding space based on a recurrent residual fusion (RRF)…