activity
20242026
most citedMORE: Multi-Organ Medical Image REconstruction Dataset

1 citations · 1 across the 11 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling

Mei Li, Huayi Zhou, Suizhi Huang +3

Regressing 3D rotations of objects from 2D images is a crucial yet challenging task, with broad applications in autonomous driving, virtual reality, and robotic control. Existing r…

cs.CV2024

Learning Multiple Representations with Inconsistency-Guided Detail Regularization for Mask-Guided Matting

Weihao Jiang, Zhaozhi Xie, Yuxiang Lu +6

Mask-guided matting networks have achieved significant improvements and have shown great potential in practical applications in recent years. However, simply learning matting repre…

cs.CV2024

View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV

Deyi Ji, Lanyun Zhu, Siqi Gao +8

In this paper, we address the challenge of Multi-Object Tracking (MOT) in moving Unmanned Aerial Vehicle (UAV) scenarios, where irregular flight trajectories, such as hovering, tur…

cs.CV2024

Task Indicating Transformer for Task-conditional Dense Predictions

Yuxiang Lu, Shalayiding Sirejiding, Bayram Bayramli +3

The task-conditional model is a distinctive stream for efficient multi-task learning. Existing works encounter a critical limitation in learning task-agnostic and task-specific rep…

cs.CV2024

YOLO-MED : Multi-Task Interaction Network for Biomedical Images

Suizhi Huang, Shalayiding Sirejiding, Yuxiang Lu +4

Object detection and semantic segmentation are pivotal components in biomedical image analysis. Current single-task networks exhibit promising outcomes in both detection and segmen…

cs.CV2024

Boosting Semi-Supervised 2D Human Pose Estimation by Revisiting Data Augmentation and Consistency Training

Huayi Zhou, Mukun Luo, Fei Jiang +3

The 2D human pose estimation (HPE) is a basic visual problem. However, its supervised learning requires massive keypoint labels, which is labor-intensive to collect. Thus, we aim a…