455 citations · 1.1k across the 14 of their papers we have counts for
14 papers · 1 filter
Vision Mamba Distillation for Low-resolution Fine-grained Image Classification
Yao Chen, Jiabao Wang, Peichao Wang +2
Low-resolution fine-grained image classification has recently made significant progress, largely thanks to the super-resolution techniques and knowledge distillation methods. Howev…
Paying more attention to local contrast: improving infrared small target detection performance via prior knowledge
Peichao Wang, Jiabao Wang, Yao Chen +3
The data-driven method for infrared small target detection (IRSTD) has achieved promising results. However, due to the small scale of infrared small target datasets and the limited…
YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-time Object Detection
Yuming Chen, Xinbin Yuan, Jiabao Wang +4
We aim at providing the object detection community with an efficient and performant object detector, termed YOLO-MS. The core design is based on a series of investigations on how m…
FewSAR: A Few-shot SAR Image Classification Benchmark
Rui Zhang, Ziqi Wang, Yang Li +2
Few-shot learning (FSL) is one of the significant and hard problems in the field of image classification. However, in contrast to the rapid development of the visible light dataset…
CrossKD: Cross-Head Knowledge Distillation for Object Detection
Jiabao Wang, Yuming Chen, Zhaohui Zheng +3
Knowledge Distillation (KD) has been validated as an effective model compression technique for learning compact object detectors. Existing state-of-the-art KD methods for object de…
Feature Chirality in Deep Learning Models
Shipeng Ji, Yang Li, Ruizhi Fu +2
As deep learning applications extensively increase by leaps and bounds, their interpretability has become increasingly prominent. As a universal property, chirality exists widely i…
MMRotate: A Rotated Object Detection Benchmark using PyTorch
Yue Zhou, Xue Yang, Gefan Zhang +9
We present an open-source toolbox, named MMRotate, which provides a coherent algorithm framework of training, inferring, and evaluation for the popular rotated object detection alg…
Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification
Jiabao Wang, Yang Li, Xiu-Shen Wei +3
Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID). Ho…
Anchor-free Oriented Proposal Generator for Object Detection
Gong Cheng, Jiabao Wang, Ke Li +4
Oriented object detection is a practical and challenging task in remote sensing image interpretation. Nowadays, oriented detectors mostly use horizontal boxes as intermedium to der…
Oriented R-CNN for Object Detection
Xingxing Xie, Gong Cheng, Jiabao Wang +2
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bo…
A Weakly-Supervised Depth Estimation Network Using Attention Mechanism
Fang Gao, Jiabao Wang, Jun Yu +2
Monocular depth estimation (MDE) is a fundamental task in many applications such as scene understanding and reconstruction. However, most of the existing methods rely on accurately…
Grafted network for person re-identification
Jiabao Wang, Yang Li, Shanshan Jiao +2
Convolutional neural networks have shown outstanding effectiveness in person re-identification (re-ID). However, the models always have large number of parameters and much computat…
A heterogeneous branch and multi-level classification network for person re-identification
Jiabao Wang, Yang Li, Yangshuo Zhang +2
Convolutional neural networks with multiple branches have recently been proved highly effective in person re-identification (re-ID). Researchers design multi-branch networks using…
Ensemble Feature for Person Re-Identification
Jiabao Wang, Yang Li, Zhuang Miao
In person re-identification (re-ID), the key task is feature representation, which is used to compute distance or similarity in prediction. Person re-ID achieves great improvement…