272 citations · 959 across the 34 of their papers we have counts for
36 papers
RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion
Zhiqiang Yan, Xiang Li, Le Hui +3
Depth completion aims to recover dense depth maps from sparse ones, where color images are often used to facilitate this task. Recent depth methods primarily focus on image guided…
AltNeRF: Learning Robust Neural Radiance Field via Alternating Depth-Pose Optimization
Kun Wang, Zhiqiang Yan, Huang Tian +4
Neural Radiance Fields (NeRF) have shown promise in generating realistic novel views from sparse scene images. However, existing NeRF approaches often encounter challenges due to t…
Creative Birds: Self-Supervised Single-View 3D Style Transfer
Renke Wang, Guimin Que, Shuo Chen +3
In this paper, we propose a novel method for single-view 3D style transfer that generates a unique 3D object with both shape and texture transfer. Our focus lies primarily on birds…
Learnable Differencing Center for Nighttime Depth Perception
Zhiqiang Yan, Yupeng Zheng, Chongyi Li +2
Depth completion is the task of recovering dense depth maps from sparse ones, usually with the help of color images. Existing image-guided methods perform well on daytime depth per…
Variable Radiance Field for Real-World Category-Specific Reconstruction from Single Image
Kun Wang, Zhiqiang Yan, Zhenyu Zhang +3
Reconstructing category-specific objects using Neural Radiance Field (NeRF) from a single image is a promising yet challenging task. Existing approaches predominantly rely on proje…
Fine-Grained Visual Prompting
Lingfeng Yang, Yueze Wang, Xiang Li +2
Vision-Language Models (VLMs), such as CLIP, have demonstrated impressive zero-shot transfer capabilities in image-level visual perception. However, these models have shown limited…