6 papers · 1 filter
Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors
Yingjie Feng, Yi Wang, Jiaze Wang +2
Self-supervised contrastive learning has emerged as a powerful paradigm for skeleton-based action recognition by enforcing consistency in the embedding space. However, existing met…
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…
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…
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…