4 citations · 5 across the 5 of their papers we have counts for
6 papers
Teaching Vision-Language-Action Models What to See and Where to Look
Yuguang Yang, Canyu Chen, Zhewen Tan +10
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…
Noise-Robust Tiny Object Localization with Flows
Huixin Sun, Linlin Yang, Ronyu Chen +4
Despite significant advances in generic object detection, a persistent performance gap remains for tiny objects compared to normal-scale objects. We demonstrate that tiny objects a…
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Yuguang Yang, Tongfei Chen, Haoyu Huang +5
Zero-shot medical detection can further improve detection performance without relying on annotated medical images even upon the fine-tuned model, showing great clinical value. Rece…
P4Q: Learning to Prompt for Quantization in Visual-language Models
Huixin Sun, Runqi Wang, Yanjing Li +4
Large-scale pre-trained Vision-Language Models (VLMs) have gained prominence in various visual and multimodal tasks, yet the deployment of VLMs on downstream application platforms…
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling
Ziming Wang, Shumin Han, Xiaodi Wang +3
Small CNN-based models usually require transferring knowledge from a large model before they are deployed in computationally resource-limited edge devices. Masked image modeling (M…
MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition
Yunhao Wang, Huixin Sun, Xiaodi Wang +6
Vision Transformer and its variants have demonstrated great potential in various computer vision tasks. But conventional vision transformers often focus on global dependency at a c…