197 citations · 279 across the 11 of their papers we have counts for
5 papers · 1 filter
Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback
Yang Chen, Yufan Shen, Wenxuan Huang +7
Multimodal Large Language Models (MLLMs) exhibit impressive performance across various visual tasks. Subsequent investigations into enhancing their visual reasoning abilities have…
SAM-SP: Self-Prompting Makes SAM Great Again
Chunpeng Zhou, Kangjie Ning, Qianqian Shen +3
The recently introduced Segment Anything Model (SAM), a Visual Foundation Model (VFM), has demonstrated impressive capabilities in zero-shot segmentation tasks across diverse natur…
Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR
Chunpeng Zhou, Kangjie Ning, Haishuai Wang +3
The application of 3D ground-penetrating radar (3D-GPR) for subgrade distress detection has gained widespread popularity. To enhance the efficiency and accuracy of detection, pione…
Hilbert Distillation for Cross-Dimensionality Networks
Dian Qin, Haishuai Wang, Zhe Liu +3
3D convolutional neural networks have revealed superior performance in processing volumetric data such as video and medical imaging. However, the competitive performance by leverag…
Dynamic Data-Free Knowledge Distillation by Easy-to-Hard Learning Strategy
Jingru Li, Sheng Zhou, Liangcheng Li +3
Data-free knowledge distillation (DFKD) is a widely-used strategy for Knowledge Distillation (KD) whose training data is not available. It trains a lightweight student model with t…