activity
20182023
most citedA Comprehensive Survey on Segment Anything Model for Vision and Beyond

47 citations · 115 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2023★ 3 cited

Hyperbolic Face Anti-Spoofing

Shuangpeng Han, Rizhao Cai, Yawen Cui +3

Learning generalized face anti-spoofing (FAS) models against presentation attacks is essential for the security of face recognition systems. Previous FAS methods usually encourage…

cs.CV2023★ 2 cited

Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape

Jiacong Xu, Yi Zhang, Jiawei Peng +17

Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife c…

cs.CV2023★ 2 cited

Visual Prompt Flexible-Modal Face Anti-Spoofing

Zitong Yu, Rizhao Cai, Yawen Cui +2

Recently, vision transformer based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems. However, multimodal face data colle…

cs.CV2023★ 47 cited

A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Chunhui Zhang, Li Liu, Yawen Cui +4

Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the ability of an AI system to perform a wide range of tasks and exhibit a level o…

cs.CV2023★ 1 cited

Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less

Rizhao Cai, Yawen Cui, Zhi Li +4

Face Anti-Spoofing (FAS) is recently studied under the continual learning setting, where the FAS models are expected to evolve after encountering the data from new domains. However…

cs.CV2023★ 5 cited

Generalized Few-Shot Continual Learning with Contrastive Mixture of Adapters

Yawen Cui, Zitong Yu, Rizhao Cai +3

The goal of Few-Shot Continual Learning (FSCL) is to incrementally learn novel tasks with limited labeled samples and preserve previous capabilities simultaneously, while current F…

cs.CV2023★ 4 cited

Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofing

Zitong Yu, Rizhao Cai, Yawen Cui +3

Recently, vision transformer (ViT) based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems. However, there are still no w…

cs.CV2023★ 6 cited

PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer

Zitong Yu, Yuming Shen, Jingang Shi +5

Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applicatio…

cs.CV2023★ 1 cited

Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental Learning

Yawen Cui, Wanxia Deng, Haoyu Chen +1

Given a model well-trained with a large-scale base dataset, Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by a…

cs.CV2022

Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry

Yawen Cui, Zitong Yu, Wei Peng +1

Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by avoiding the overfitting and catastrophic forgetting simultan…

cs.CV2018★ 44 cited

Factorizable Net: An Efficient Subgraph-based Framework for Scene Graph Generation

Yikang Li, Wanli Ouyang, Bolei Zhou +3

Generating scene graph to describe all the relations inside an image gains increasing interests these years. However, most of the previous methods use complicated structures with s…