317 citations · 1.3k across the 37 of their papers we have counts for
11 papers · 1 filter
Towards Overcoming False Positives in Visual Relationship Detection
Daisheng Jin, Xiao Ma, Chongzhi Zhang +8
In this paper, we investigate the cause of the high false positive rate in Visual Relationship Detection (VRD). We observe that during training, the relationship proposal distribut…
BiPointNet: Binary Neural Network for Point Clouds
Haotong Qin, Zhongang Cai, Mingyuan Zhang +5
To alleviate the resource constraint for real-time point cloud applications that run on edge devices, in this paper we present BiPointNet, the first model binarization approach for…
BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation
Xianghui Yang, Bairun Wang, Kaige Chen +4
Few-shot segmentation focuses on the generalization of models to segment unseen object instances with limited training samples. Although tremendous improvements have been achieved,…
Performance Optimization for Federated Person Re-identification via Benchmark Analysis
Weiming Zhuang, Yonggang Wen, Xuesen Zhang +5
Federated learning is a privacy-preserving machine learning technique that learns a shared model across decentralized clients. It can alleviate privacy concerns of personal re-iden…
MessyTable: Instance Association in Multiple Camera Views
Zhongang Cai, Junzhe Zhang, Daxuan Ren +5
We present an interesting and challenging dataset that features a large number of scenes with messy tables captured from multiple camera views. Each scene in this dataset is highly…
Balanced Meta-Softmax for Long-Tailed Visual Recognition
Jiawei Ren, Cunjun Yu, Shunan Sheng +4
Deep classifiers have achieved great success in visual recognition. However, real-world data is long-tailed by nature, leading to the mismatch between training and testing distribu…
Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction
Cunjun Yu, Xiao Ma, Jiawei Ren +2
Understanding crowd motion dynamics is critical to real-world applications, e.g., surveillance systems and autonomous driving. This is challenging because it requires effectively m…
Cheaper Pre-training Lunch: An Efficient Paradigm for Object Detection
Dongzhan Zhou, Xinchi Zhou, Hongwen Zhang +2
In this paper, we propose a general and efficient pre-training paradigm, Montage pre-training, for object detection. Montage pre-training needs only the target detection dataset wh…
EcoNAS: Finding Proxies for Economical Neural Architecture Search
Dongzhan Zhou, Xinchi Zhou, Wenwei Zhang +4
Neural Architecture Search (NAS) achieves significant progress in many computer vision tasks. While many methods have been proposed to improve the efficiency of NAS, the search pro…
GTC: Guided Training of CTC Towards Efficient and Accurate Scene Text Recognition
Wenyang Hu, Xiaocong Cai, Jun Hou +2
Connectionist Temporal Classification (CTC) and attention mechanism are two main approaches used in recent scene text recognition works. Compared with attention-based methods, CTC…
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identification
Yushi Lan, Yuan Liu, Maoqing Tian +4
Although person re-identification (ReID) has achieved significant improvement recently by enforcing part alignment, it is still a challenging task when it comes to distinguishing v…