122 citations · 419 across the 23 of their papers we have counts for
14 papers · 1 filter
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty
Yuan Zhang, Weihua Chen, Yichen Lu +3
Knowledge distillation is an effective paradigm for boosting the performance of pocket-size model, especially when multiple teacher models are available, the student would break th…
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Weihua Chen, Xianzhe Xu, Jian Jia +5
Human-centric visual tasks have attracted increasing research attention due to their widespread applications. In this paper, we aim to learn a general human representation from mas…
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition
Junyan Wang, Zhenhong Sun, Yichen Qian +5
3D convolution neural networks (CNNs) have been the prevailing option for video recognition. To capture the temporal information, 3D convolutions are computed along the sequences,…
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network
Xuan Shen, Yaohua Wang, Ming Lin +4
The rapid advances in Vision Transformer (ViT) refresh the state-of-the-art performances in various vision tasks, overshadowing the conventional CNN-based models. This ignites a fe…
DAMO-YOLO : A Report on Real-Time Object Detection Design
Xianzhe Xu, Yiqi Jiang, Weihua Chen +3
In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO series. DAMO-YOLO is exten…
Robust Graph Structure Learning via Multiple Statistical Tests
Yaohua Wang, FangYi Zhang, Ming Lin +3
Graph structure learning aims to learn connectivity in a graph from data. It is particularly important for many computer vision related tasks since no explicit graph structure is a…
GiraffeDet: A Heavy-Neck Paradigm for Object Detection
Yiqi Jiang, Zhiyu Tan, Junyan Wang +3
In conventional object detection frameworks, a backbone body inherited from image recognition models extracts deep latent features and then a neck module fuses these latent feature…
Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
Yaohua Wang, Yaobin Zhang, Fangyi Zhang +4
Face clustering has attracted rising research interest recently to take advantage of massive amounts of face images on the web. State-of-the-art performance has been achieved by Gr…
TAGPerson: A Target-Aware Generation Pipeline for Person Re-identification
Kai Chen, Weihua Chen, Tao He +5
Nowadays, real data in person re-identification (ReID) task is facing privacy issues, e.g., the banned dataset DukeMTMC-ReID. Thus it becomes much harder to collect real data for R…
MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection
Zhenhong Sun, Ming Lin, Xiuyu Sun +3
In object detection, the detection backbone consumes more than half of the overall inference cost. Recent researches attempt to reduce this cost by optimizing the backbone architec…
Exploring the Quality of GAN Generated Images for Person Re-Identification
Yiqi Jiang, Weihua Chen, Xiuyu Sun +3
Recently, GAN based method has demonstrated strong effectiveness in generating augmentation data for person re-identification (ReID), on account of its ability to bridge the gap be…
Learning to Cluster Faces via Transformer
Jinxing Ye, Xioajiang Peng, Baigui Sun +4
Face clustering is a useful tool for applications like automatic face annotation and retrieval. The main challenge is that it is difficult to cluster images from the same identity…
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition
Ming Lin, Pichao Wang, Zhenhong Sun +5
Accuracy predictor is a key component in Neural Architecture Search (NAS) for ranking architectures. Building a high-quality accuracy predictor usually costs enormous computation.…
Neural Architecture Design for GPU-Efficient Networks
Ming Lin, Hesen Chen, Xiuyu Sun +3
Many mission-critical systems are based on GPU for inference. It requires not only high recognition accuracy but also low latency in responding time. Although many studies are devo…