most citedDoF-NeRF: Depth-of-Field Meets Neural Radiance Fields

33 citations · 156 across the 21 of their papers we have counts for

collaborators

21 papers

cs.CV20231 cited

When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo

Tianqi Liu, Xinyi Ye, Weiyue Zhao +3

Learning-based multi-view stereo (MVS) method heavily relies on feature matching, which requires distinctive and descriptive representations. An effective solution is to apply non-…

cs.CV202327 cited

Learning to Upsample by Learning to Sample

Wenze Liu, Hao Lu, Hongtao Fu +1

We present DySample, an ultra-lightweight and effective dynamic upsampler. While impressive performance gains have been witnessed from recent kernel-based dynamic upsamplers such a…

cs.CV20234 cited

Point-Query Quadtree for Crowd Counting, Localization, and More

Chengxin Liu, Hao Lu, Zhiguo Cao +1

We show that crowd counting can be viewed as a decomposable point querying process. This formulation enables arbitrary points as input and jointly reasons whether the points are cr…

cs.CV202314 cited

Make-It-4D: Synthesizing a Consistent Long-Term Dynamic Scene Video from a Single Image

Liao Shen, Xingyi Li, Huiqiang Sun +4

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camer…

cs.CV20239 cited

Diffusion-Augmented Depth Prediction with Sparse Annotations

Jiaqi Li, Yiran Wang, Zihao Huang +4

Depth estimation aims to predict dense depth maps. In autonomous driving scenes, sparsity of annotations makes the task challenging. Supervised models produce concave objects due t…

cs.CV202313 cited

The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World

Weiyun Wang, Min Shi, Qingyun Li +11

We present the All-Seeing (AS) project: a large-scale data and model for recognizing and understanding everything in the open world. Using a scalable data engine that incorporates…