423 citations · 1.1k across the 44 of their papers we have counts for
10 papers · 1 filter
3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views
Evangelos Ververas, Polydefkis Gkagkos, Jiankang Deng +3
Developing gaze estimation models that generalize well to unseen domains and in-the-wild conditions remains a challenge with no known best solution. This is mostly due to the diffi…
Physically-Based Face Rendering for NIR-VIS Face Recognition
Yunqi Miao, Alexandros Lattas, Jiankang Deng +2
Near infrared (NIR) to Visible (VIS) face matching is challenging due to the significant domain gaps as well as a lack of sufficient data for cross-modality model training. To over…
Deep Face Restoration: A Survey
Tao Wang, Kaihao Zhang, Jiankang Deng +3
Face Restoration (FR) aims to restore High-Quality (HQ) faces from Low-Quality (LQ) input images, which is a domain-specific image restoration problem in the low-level computer vis…
Inverse Image Frequency for Long-tailed Image Recognition
Konstantinos Panagiotis Alexandridis, Shan Luo, Anh Nguyen +2
The long-tailed distribution is a common phenomenon in the real world. Extracted large scale image datasets inevitably demonstrate the long-tailed property and models trained with…
Redesigning Multi-Scale Neural Network for Crowd Counting
Zhipeng Du, Miaojing Shi, Jiankang Deng +1
Perspective distortions and crowd variations make crowd counting a challenging task in computer vision. To tackle it, many previous works have used multi-scale architecture in deep…
Long-tailed Instance Segmentation using Gumbel Optimized Loss
Konstantinos Panagiotis Alexandridis, Jiankang Deng, Anh Nguyen +1
Major advancements have been made in the field of object detection and segmentation recently. However, when it comes to rare categories, the state-of-the-art methods fail to detect…
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchma…
Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC
Xiang An, Jiankang Deng, Jia Guo +4
Learning discriminative deep feature embeddings by using million-scale in-the-wild datasets and margin-based softmax loss is the current state-of-the-art approach for face recognit…
Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing
Qingping Zheng, Jiankang Deng, Zheng Zhu +2
This paper probes intrinsic factors behind typical failure cases (e.g. spatial inconsistency and boundary confusion) produced by the existing state-of-the-art method in face parsin…
Facial Geometric Detail Recovery via Implicit Representation
Xingyu Ren, Alexandros Lattas, Baris Gecer +4
Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries thr…