3 citations · 4 across the 6 of their papers we have counts for
6 papers
HCPM: Hierarchical Candidates Pruning for Efficient Detector-Free Matching
Ying Chen, Yong Liu, Kai Wu +5
Deep learning-based image matching methods play a crucial role in computer vision, yet they often suffer from substantial computational demands. To tackle this challenge, we presen…
FusionDepth: Complement Self-Supervised Monocular Depth Estimation with Cost Volume
Zhuofei Huang, Jianlin Liu, Shang Xu +2
Multi-view stereo depth estimation based on cost volume usually works better than self-supervised monocular depth estimation except for moving objects and low-textured surfaces. So…
Scatter Points in Space: 3D Detection from Multi-view Monocular Images
Jianlin Liu, Zhuofei Huang, Dihe Huang +3
3D object detection from monocular image(s) is a challenging and long-standing problem of computer vision. To combine information from different perspectives without troublesome 2D…
Adaptive Assignment for Geometry Aware Local Feature Matching
Dihe Huang, Ying Chen, Shang Xu +5
The detector-free feature matching approaches are currently attracting great attention thanks to their excellent performance. However, these methods still struggle at large-scale a…
UniInst: Unique Representation for End-to-End Instance Segmentation
Yimin Ou, Rui Yang, Lufan Ma +5
Existing instance segmentation methods have achieved impressive performance but still suffer from a common dilemma: redundant representations (e.g., multiple boxes, grids, and anch…
Guide Local Feature Matching by Overlap Estimation
Ying Chen, Dihe Huang, Shang Xu +2
Local image feature matching under large appearance, viewpoint, and distance changes is challenging yet important. Conventional methods detect and match tentative local features ac…