71 citations · 129 across the 10 of their papers we have counts for
10 papers
PaCo-FR: Patch-Pixel Aligned End-to-End Codebook Learning for Facial Representation Pre-training
Yin Xie, Zhichao Chen, Zeyu Xiao +7
Facial representation pre-training is crucial for tasks like facial recognition, expression analysis, and virtual reality. However, existing methods face three key challenges: (1)…
High-Fidelity Facial Albedo Estimation via Texture Quantization
Zimin Ran, Xingyu Ren, Xiang An +6
Recent 3D face reconstruction methods have made significant progress in shape estimation, but high-fidelity facial albedo reconstruction remains challenging. Existing methods depen…
Monocular Identity-Conditioned Facial Reflectance Reconstruction
Xingyu Ren, Jiankang Deng, Yuhao Cheng +5
Recent 3D face reconstruction methods have made remarkable advancements, yet there remain huge challenges in monocular high-quality facial reflectance reconstruction. Existing meth…
IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models
Siying Cui, Jia Guo, Xiang An +4
Leveraging Stable Diffusion for the generation of personalized portraits has emerged as a powerful and noteworthy tool, enabling users to create high-fidelity, custom character ava…
ALIP: Adaptive Language-Image Pre-training with Synthetic Caption
Kaicheng Yang, Jiankang Deng, Xiang An +5
Contrastive Language-Image Pre-training (CLIP) has significantly boosted the performance of various vision-language tasks by scaling up the dataset with image-text pairs collected…
Unicom: Universal and Compact Representation Learning for Image Retrieval
Xiang An, Jiankang Deng, Kaicheng Yang +5
Modern image retrieval methods typically rely on fine-tuning pre-trained encoders to extract image-level descriptors. However, the most widely used models are pre-trained on ImageN…
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…
Masked Face Recognition Challenge: The InsightFace Track Report
Jiankang Deng, Jia Guo, Xiang An +2
During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which poses a huge challenge to deep face recognition. In this workshop, we organize Masked Face Reco…
Masked Face Recognition Challenge: The WebFace260M Track Report
Zheng Zhu, Guan Huang, Jiankang Deng +9
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…
Sample and Computation Redistribution for Efficient Face Detection
Jia Guo, Jiankang Deng, Alexandros Lattas +1
Although tremendous strides have been made in uncontrolled face detection, efficient face detection with a low computation cost as well as high precision remains an open challenge.…