17 citations · 71 across the 12 of their papers we have counts for
12 papers
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image
Yijin Li, Xinyang Liu, Wenqi Dong +5
Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-energy and have been massively deployed on mobile devices for the purposes like autofocus, obstacle detection,…
NeuralMarker: A Framework for Learning General Marker Correspondence
Zhaoyang Huang, Xiaokun Pan, Weihong Pan +5
We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker. Conventionally, this problem is addresse…
OnePose: One-Shot Object Pose Estimation without CAD Models
Jiaming Sun, Zihao Wang, Siyu Zhang +4
We propose a new method named OnePose for object pose estimation. Unlike existing instance-level or category-level methods, OnePose does not rely on CAD models and can handle objec…
Neural 3D Scene Reconstruction with the Manhattan-world Assumption
Haoyu Guo, Sida Peng, Haotong Lin +4
This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results on textured objects,…
Neural Rendering in a Room: Amodal 3D Understanding and Free-Viewpoint Rendering for the Closed Scene Composed of Pre-Captured Objects
Bangbang Yang, Yinda Zhang, Yijin Li +4
We, as human beings, can understand and picture a familiar scene from arbitrary viewpoints given a single image, whereas this is still a grand challenge for computers. We hereby pr…
RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization
Yan Xu, Kwan-Yee Lin, Guofeng Zhang +2
6-DoF object pose estimation from a monocular image is challenging, and a post-refinement procedure is generally needed for high-precision estimation. In this paper, we propose a f…