637 citations · 1k across the 24 of their papers we have counts for
25 papers
Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning
Xiang Yuan, Gong Cheng, Kebing Yan +2
The past few years have witnessed the immense success of object detection, while current excellent detectors struggle on tackling size-limited instances. Concretely, the well-known…
Model-agnostic explainable artificial intelligence for object detection in image data
Milad Moradi, Ke Yan, David Colwell +2
In recent years, deep neural networks have been widely used for building high-performance Artificial Intelligence (AI) systems for computer vision applications. Object detection is…
Few-Shot Object Detection via Variational Feature Aggregation
Jiaming Han, Yuqiang Ren, Jian Ding +2
As few-shot object detectors are often trained with abundant base samples and fine-tuned on few-shot novel examples,the learned models are usually biased to base classes and sensit…
Towards Large-Scale Small Object Detection: Survey and Benchmarks
Gong Cheng, Xiang Yuan, Xiwen Yao +4
With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactor…
Location-free Human Pose Estimation
Xixia Xu, Yingguo Gao, Ke Yan +2
Human pose estimation (HPE) usually requires large-scale training data to reach high performance. However, it is rather time-consuming to collect high-quality and fine-grained anno…
SIOD: Single Instance Annotated Per Category Per Image for Object Detection
Hanjun Li, Xingjia Pan, Ke Yan +2
Object detection under imperfect data receives great attention recently. Weakly supervised object detection (WSOD) suffers from severe localization issues due to the lack of instan…