3 papers
cs.CV2026
Towards Photorealistic and Efficient Bokeh Rendering via Diffusion Framework
Linxiao Shi, Siming Zheng, Zerong Wang +5
Existing mobile devices are constrained by compact optical designs, such as small apertures, which make it difficult to produce natural, optically realistic bokeh effects. Although…
cs.CV2025
DepthMaster: Taming Diffusion Models for Monocular Depth Estimation
Ziyang Song, Zerong Wang, Bo Li +5
Monocular depth estimation within the diffusion-denoising paradigm demonstrates impressive generalization ability but suffers from low inference speed. Recent methods adopt a singl…
cs.CV2024
Mono-ViFI: A Unified Learning Framework for Self-supervised Single- and Multi-frame Monocular Depth Estimation
Jinfeng Liu, Lingtong Kong, Bo Li +3
Self-supervised monocular depth estimation has gathered notable interest since it can liberate training from dependency on depth annotations. In monocular video training case, rece…