5 papers
Towards UAV Image Dehazing: A UAV Atmospheric Scattering Model, Benchmark, and Geometry-Aware Deep Unfolding Network
Wenxuan Fang, Jiangwei Weng, Yu Zheng +5
In UAV applications, haze significantly obscures distant details and weaken structural information, hindering the recovery of details. Current UAV scenarios still face two key chal…
Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance
Junkai Fan, Jiangwei Weng, Kun Wang +4
Real driving-video dehazing poses a significant challenge due to the inherent difficulty in acquiring precisely aligned hazy/clear video pairs for effective model training, especia…
Learning Inverse Laplacian Pyramid for Progressive Depth Completion
Kun Wang, Zhiqiang Yan, Junkai Fan +2
Depth completion endeavors to reconstruct a dense depth map from sparse depth measurements, leveraging the information provided by a corresponding color image. Existing approaches…
Depth-Centric Dehazing and Depth-Estimation from Real-World Hazy Driving Video
Junkai Fan, Kun Wang, Zhiqiang Yan +4
In this paper, we study the challenging problem of simultaneously removing haze and estimating depth from real monocular hazy videos. These tasks are inherently complementary: enha…
DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain
Kun Wang, Zhiqiang Yan, Junkai Fan +4
In this paper, we introduce DCDepth, a novel framework for the long-standing monocular depth estimation task. Moving beyond conventional pixel-wise depth estimation in the spatial…