25 citations · 30 across the 2 of their papers we have counts for
6 papers · 1 filter
TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking
Peng Chu, Jiang Wang, Quanzeng You +2
Tracking multiple objects in videos relies on modeling the spatial-temporal interactions of the objects. In this paper, we propose a solution named TransMOT, which leverages powerf…
RC-DARTS: Resource Constrained Differentiable Architecture Search
Xiaojie Jin, Jiang Wang, Joshua Slocum +4
Recent advances show that Neural Architectural Search (NAS) method is able to find state-of-the-art image classification deep architectures. In this paper, we consider the one-shot…
Adversarial Examples Improve Image Recognition
Cihang Xie, Mingxing Tan, Boqing Gong +3
Adversarial examples are commonly viewed as a threat to ConvNets. Here we present an opposite perspective: adversarial examples can be used to improve image recognition models if h…
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection
JIyang Gao, Jiang Wang, Shengyang Dai +2
The labeling cost of large number of bounding boxes is one of the main challenges for training modern object detectors. To reduce the dependence on expensive bounding box annotatio…
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition
Xiao Liu, Jiang Wang, Shilei Wen +2
A key challenge in fine-grained recognition is how to find and represent discriminative local regions. Recent attention models are capable of learning discriminative region localiz…
CNN-RNN: A Unified Framework for Multi-label Image Classification
Jiang Wang, Yi Yang, Junhua Mao +3
While deep convolutional neural networks (CNNs) have shown a great success in single-label image classification, it is important to note that real world images generally contain mu…