11 papers · 1 filter
EVO-WAM: Evolving World Action Models through Video-Action Verification
Shiyang Zhou, Xionghao Wu, Wenbo Li +11
Improving robot policies on new tasks without collecting additional expert demonstrations remains a central challenge in robot learning. World action models (WAMs) use broad video…
Video as Natural Augmentation: Towards Unified AI-Generated Image and Video Detection
Zhengcen Li, Chenyang Jiang, Liangxu Su +4
AI-generated content (AIGC) is rapidly improving, creating an urgent need for detectors that generalize across data sources, deployment pipelines, and visual modalities. A strongly…
Preserving Forgery Artifacts: AI-Generated Video Detection at Native Scale
Zhengcen Li, Chenyang Jiang, Hang Zhao +7
The rapid advancement of video generation models has enabled the creation of highly realistic synthetic media, raising significant societal concerns regarding the spread of misinfo…
Consistency Beyond Contrast: Enhancing Open-Vocabulary Object Detection Robustness via Contextual Consistency Learning
Bozhao Li, Shaocong Wu, Tong Shao +4
Recent advances in open-vocabulary object detection focus primarily on two aspects: scaling up datasets and leveraging contrastive learning to align language and vision modalities.…
SODA: Sensitivity-Oriented Dynamic Acceleration for Diffusion Transformer
Tong Shao, Yusen Fu, Guoying Sun +3
Diffusion Transformers have become a dominant paradigm in visual generation, yet their low inference efficiency remains a key bottleneck hindering further advancement. Among common…
Beyond Static Cropping: Layer-Adaptive Visual Localization and Decoding Enhancement
Zipeng Zhu, Zhanghao Hu, Qinglin Zhu +5
Large Vision-Language Models (LVLMs) have advanced rapidly by aligning visual patches with the text embedding space, but a fixed visual-token budget forces images to be resized to…
Plug-and-Play Fidelity Optimization for Diffusion Transformer Acceleration via Cumulative Error Minimization
Tong Shao, Yusen Fu, Guoying Sun +3
Although Diffusion Transformer (DiT) has emerged as a predominant architecture for image and video generation, its iterative denoising process results in slow inference, which hind…
Rectifying Soft-Label Entangled Bias in Long-Tailed Dataset Distillation
Chenyang Jiang, Hang Zhao, Xinyu Zhang +4
Dataset distillation compresses large-scale datasets into compact, highly informative synthetic data, significantly reducing storage and training costs. However, existing research…
KAN or MLP? Point Cloud Shows the Way Forward
Yan Shi, Qingdong He, Yijun Liu +2
Multi-Layer Perceptrons (MLPs) have become one of the fundamental architectural component in point cloud analysis due to its effective feature learning mechanism. However, when pro…
Typicalness-Aware Learning for Failure Detection
Yijun Liu, Jiequan Cui, Zhuotao Tian +4
Deep neural networks (DNNs) often suffer from the overconfidence issue, where incorrect predictions are made with high confidence scores, hindering the applications in critical sys…
Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation
Tong Shao, Zhuotao Tian, Hang Zhao +1
CLIP, as a vision-language model, has significantly advanced Open-Vocabulary Semantic Segmentation (OVSS) with its zero-shot capabilities. Despite its success, its application to O…