4 citations · 7 across the 10 of their papers we have counts for
7 papers · 2 filters
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…
Completion as Enhancement: A Degradation-Aware Selective Image Guided Network for Depth Completion
Zhiqiang Yan, Zhengxue Wang, Kun Wang +2
In this paper, we introduce the Selective Image Guided Network (SigNet), a novel degradation-aware framework that transforms depth completion into depth enhancement for the first t…
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…
Deep Height Decoupling for Precise Vision-based 3D Occupancy Prediction
Yuan Wu, Zhiqiang Yan, Zhengxue Wang +3
The task of vision-based 3D occupancy prediction aims to reconstruct 3D geometry and estimate its semantic classes from 2D color images, where the 2D-to-3D view transformation is a…
MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space
Jiangwei Weng, Zhiqiang Yan, Ying Tai +3
Recent advances in low light image enhancement have been dominated by Retinex-based learning framework, leveraging convolutional neural networks (CNNs) and Transformers. However, t…
Tri-Perspective View Decomposition for Geometry-Aware Depth Completion
Zhiqiang Yan, Yuankai Lin, Kun Wang +5
Depth completion is a vital task for autonomous driving, as it involves reconstructing the precise 3D geometry of a scene from sparse and noisy depth measurements. However, most ex…