13 papers · 1 filter
Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy
Yuan Wu, Zhiqiang Yan, Jiawei Lian +2
3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a crucial step in bridging image…
SpatioTemporal Difference Network for Video Depth Super-Resolution
Zhengxue Wang, Yuan Wu, Xiang Li +2
Depth super-resolution has achieved impressive performance, and the incorporation of multi-frame information further enhances reconstruction quality. Nevertheless, statistical anal…
See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy Prediction
Yuan Wu, Zhiqiang Yan, Yigong Zhang +2
Occupancy prediction aims to estimate the 3D spatial distribution of occupied regions along with their corresponding semantic labels. Existing vision-based methods perform well on…
DuCos: Duality Constrained Depth Super-Resolution via Foundation Model
Zhiqiang Yan, Zhengxue Wang, Haoye Dong +3
We introduce DuCos, a novel depth super-resolution framework grounded in Lagrangian duality theory, offering a flexible integration of multiple constraints and reconstruction objec…
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…