42 citations · 83 across the 12 of their papers we have counts for
4 papers · 1 filter
A Closer Look at the Explainability of Contrastive Language-Image Pre-training
Yi Li, Hualiang Wang, Yiqun Duan +2
Contrastive language-image pre-training (CLIP) is a powerful vision-language model that has shown great benefits for various tasks. However, we have identified some issues with its…
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth Estimation
Yiqun Duan, Xianda Guo, Zheng Zhu
Monocular depth estimation is a challenging task that predicts the pixel-wise depth from a single 2D image. Current methods typically model this problem as a regression or classifi…
Exploring Visual Interpretability for Contrastive Language-Image Pre-training
Yi Li, Hualiang Wang, Yiqun Duan +2
Contrastive Language-Image Pre-training (CLIP) learns rich representations via readily available supervision of natural language. It improves the performance of downstream vision t…
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation
Yi Li, Yiqun Duan, Zhanghui Kuang +3
Weakly-Supervised Semantic Segmentation (WSSS) segments objects without a heavy burden of dense annotation. While as a price, generated pseudo-masks exist obvious noisy pixels, whi…