193 citations · 726 across the 54 of their papers we have counts for
11 papers · 1 filter
Frequency Consistent Adaptation for Real World Super Resolution
Xiaozhong Ji, Guangpin Tao, Yun Cao +5
Recent deep-learning based Super-Resolution (SR) methods have achieved remarkable performance on images with known degradation. However, these methods always fail in real-world sce…
They are Not Completely Useless: Towards Recycling Transferable Unlabeled Data for Class-Mismatched Semi-Supervised Learning
Zhuo Huang, Ying Tai, Chengjie Wang +2
Semi-Supervised Learning (SSL) with mismatched classes deals with the problem that the classes-of-interests in the limited labeled data is only a subset of the classes in massive u…
Face Anti-Spoofing Via Disentangled Representation Learning
Ke-Yue Zhang, Taiping Yao, Jian Zhang +6
Face anti-spoofing is crucial to security of face recognition systems. Previous approaches focus on developing discriminative models based on the features extracted from images, wh…
Adversarial Semantic Data Augmentation for Human Pose Estimation
Yanrui Bin, Xuan Cao, Xinya Chen +7
Human pose estimation is the task of localizing body keypoints from still images. The state-of-the-art methods suffer from insufficient examples of challenging cases such as symmet…
Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking
Jinlong Peng, Changan Wang, Fangbin Wan +7
Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or…
Temporal Distinct Representation Learning for Action Recognition
Junwu Weng, Donghao Luo, Yabiao Wang +6
Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos. However…
Collaborative Learning for Faster StyleGAN Embedding
Shanyan Guan, Ying Tai, Bingbing Ni +3
The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator. Embedding a given image back to the l…
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition
Yuge Huang, Yuhan Wang, Ying Tai +5
As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability. More recent…
ASFD: Automatic and Scalable Face Detector
Bin Zhang, Jian Li, Yabiao Wang +7
In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design…
Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation
Liang Liu, Jiangning Zhang, Ruifei He +7
Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods. However, the objective of…
Improving Face Recognition from Hard Samples via Distribution Distillation Loss
Yuge Huang, Pengcheng Shen, Ying Tai +5
Large facial variations are the main challenge in face recognition. To this end, previous variation-specific methods make full use of task-related prior to design special network l…