output
20062025
most citedDistance-IoU Loss: Faster and Better Learning for Bounding Box Regression

961 citations

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78 papers · 1 filter

cs.CV2025

AM-Net: Adaptively Aligned Multi-Scale Moment for Few-Shot Action Recognition

Zilin Gao, Qilong Wang, Bingbing Zhang +2

Thanks to capability to alleviate the cost of large-scale annotation, few-shot action recognition (FSAR) has attracted increased attention of researchers in recent years. Existing…

cs.CV202545 cited

Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation

Qiangguo Jin, Hui Cui, Junbo Wang +7

Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-l…

cs.CV20257 cited

NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation

Xuzhi Wang, Wei Feng, Lingdong Kong +1

LiDAR semantic segmentation plays a vital role in autonomous driving. Existing voxel-based methods for LiDAR semantic segmentation apply uniform partition to the 3D LiDAR point clo…

cs.CV2024

Differential Alignment for Domain Adaptive Object Detection

Xinyu He, Xinhui Li, Xiaojie Guo

Domain adaptive object detection (DAOD) aims to generalize an object detector trained on labeled source-domain data to a target domain without annotations, the core principle of wh…

cs.CV20244 cited

Multi-Level Correlation Network For Few-Shot Image Classification

Yunkai Dang, Min Zhang, Zhengyu Chen +4

Few-shot image classification(FSIC) aims to recognize novel classes given few labeled images from base classes. Recent works have achieved promising classification performance, esp…

cs.CV20243 cited

Dynamic Brightness Adaptation for Robust Multi-modal Image Fusion

Yiming Sun, Bing Cao, Pengfei Zhu +1

Infrared and visible image fusion aim to integrate modality strengths for visually enhanced, informative images. Visible imaging in real-world scenarios is susceptible to dynamic e…