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DMS:Diffusion-Based Multi-Baseline Stereo Generation for Improving Self-Supervised Depth Estimation
Zihua Liu, Yizhou Li, Songyan Zhang +1
While supervised stereo matching and monocular depth estimation have advanced significantly with learning-based algorithms, self-supervised methods using stereo images as supervisi…
Segmentation-Guided Neural Radiance Fields for Novel Street View Synthesis
Yizhou Li, Yusuke Monno, Masatoshi Okutomi +3
Recent advances in Neural Radiance Fields (NeRF) have shown great potential in 3D reconstruction and novel view synthesis, particularly for indoor and small-scale scenes. However,…
TDM: Temporally-Consistent Diffusion Model for All-in-One Real-World Video Restoration
Yizhou Li, Zihua Liu, Yusuke Monno +1
In this paper, we propose the first diffusion-based all-in-one video restoration method that utilizes the power of a pre-trained Stable Diffusion and a fine-tuned ControlNet. Our m…
CFDNet: A Generalizable Foggy Stereo Matching Network with Contrastive Feature Distillation
Zihua Liu, Yizhou Li, Masatoshi Okutomi
Stereo matching under foggy scenes remains a challenging task since the scattering effect degrades the visibility and results in less distinctive features for dense correspondence…
Global Occlusion-Aware Transformer for Robust Stereo Matching
Zihua Liu, Yizhou Li, Masatoshi Okutomi
Despite the remarkable progress facilitated by learning-based stereo-matching algorithms, the performance in the ill-conditioned regions, such as the occluded regions, remains a bo…