1 citations · 1 across the 1 of their papers we have counts for
6 papers
Coarse-to-Fine: A Hybrid Self-Supervised Method for Non-rigid 3D Shape Matching
Feifan Luo, Ting Li, Zhao Li +1
Non-rigid 3D shape matching is a fundamental task in computer vision and graphics. In this paper, we propose a hybrid self-supervised method based on a coarse-to-fine strategy, whi…
MGDFIS: Multi-scale Global-detail Feature Integration Strategy for Small Object Detection
Yuxiang Wang, Xuecheng Bai, Chuanzhi Xu +2
Small-object detection in Unmanned Aerial Vehicle (UAV) imagery requires preserving weak local evidence while using broader context to separate tiny foreground targets from clutter…
MonoPCC: Photometric-invariant Cycle Constraint for Monocular Depth Estimation of Endoscopic Images
Zhiwei Wang, Ying Zhou, Shiquan He +6
Photometric constraint is indispensable for self-supervised monocular depth estimation. It involves warping a source image onto a target view using estimated depth&pose, and then m…
MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint
Qiang Hu, Zhenyu Yi, Ying Zhou +4
We propose MonoBox, an innovative box-supervised segmentation method constrained by monotonicity to liberate its training from the user-unfriendly box-tightness assumption. In cont…
IA2U: A Transfer Plugin with Multi-Prior for In-Air Model to Underwater
Jingchun Zhou, Qilin Gai, Kin-man Lam +1
In underwater environments, variations in suspended particle concentration and turbidity cause severe image degradation, posing significant challenges to image enhancement (IE) and…
IBoxCLA: Towards Robust Box-supervised Segmentation of Polyp via Improved Box-dice and Contrastive Latent-anchors
Qiang Hu, Ying Chen, Hongkuan Shi +2
Box-supervised polyp segmentation attracts increasing attention for its cost-effective potential. Existing solutions often rely on learning-free methods or pretrained models to lab…