activity
20102023
most citedSession-based Recommendation with Graph Neural Networks

1.5k citations · 3.2k across the 75 of their papers we have counts for

collaborators

75 papers

cs.CV2023★ 11 cited

RiDDLE: Reversible and Diversified De-identification with Latent Encryptor

Dongze Li, Wei Wang, Kang Zhao +2

This work presents RiDDLE, short for Reversible and Diversified De-identification with Latent Encryptor, to protect the identity information of people from being misused. Built upo…

cs.CV2023★ 2 cited

Collaborative Feature Learning for Fine-grained Facial Forgery Detection and Segmentation

Weinan Guan, Wei Wang, Jing Dong +2

Detecting maliciously falsified facial images and videos has attracted extensive attention from digital-forensics and computer-vision communities. An important topic in manipulatio…

cs.CV2023

CFFT-GAN: Cross-domain Feature Fusion Transformer for Exemplar-based Image Translation

Tianxiang Ma, Bingchuan Li, Wei Liu +3

Exemplar-based image translation refers to the task of generating images with the desired style, while conditioning on certain input image. Most of the current methods learn the co…

cs.CV2023★ 1 cited

Semantic 3D-aware Portrait Synthesis and Manipulation Based on Compositional Neural Radiance Field

Tianxiang Ma, Bingchuan Li, Qian He +2

Recently 3D-aware GAN methods with neural radiance field have developed rapidly. However, current methods model the whole image as an overall neural radiance field, which limits th…

cs.CV2022★ 8 cited

Human Image Generation: A Comprehensive Survey

Zhen Jia, Zhang Zhang, Liang Wang +1

Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great ac…

cs.CV2022★ 11 cited

BEVBert: Multimodal Map Pre-training for Language-guided Navigation

Dong An, Yuankai Qi, Yangguang Li +4

Large-scale pre-training has shown promising results on the vision-and-language navigation (VLN) task. However, most existing pre-training methods employ discrete panoramas to lear…