10 citations · 25 across the 15 of their papers we have counts for
15 papers
ReST: A Reconfigurable Spatial-Temporal Graph Model for Multi-Camera Multi-Object Tracking
Cheng-Che Cheng, Min-Xuan Qiu, Chen-Kuo Chiang +1
Multi-Camera Multi-Object Tracking (MC-MOT) utilizes information from multiple views to better handle problems with occlusion and crowded scenes. Recently, the use of graph-based a…
A Closer Look at Geometric Temporal Dynamics for Face Anti-Spoofing
Chih-Jung Chang, Yaw-Chern Lee, Shih-Hsuan Yao +4
Face anti-spoofing (FAS) is indispensable for a face recognition system. Many texture-driven countermeasures were developed against presentation attacks (PAs), but the performance…
Interaction-Aware Prompting for Zero-Shot Spatio-Temporal Action Detection
Wei-Jhe Huang, Jheng-Hsien Yeh, Min-Hung Chen +2
The goal of spatial-temporal action detection is to determine the time and place where each person's action occurs in a video and classify the corresponding action category. Most o…
Kinship Representation Learning with Face Componential Relation
Weng-Tai Su, Min-Hung Chen, Chien-Yi Wang +2
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem. However, most previous methods foc…
Generalized Face Anti-Spoofing via Multi-Task Learning and One-Side Meta Triplet Loss
Chu-Chun Chuang, Chien-Yi Wang, Shang-Hong Lai
With the increasing variations of face presentation attacks, model generalization becomes an essential challenge for a practical face anti-spoofing system. This paper presents a ge…
MixFairFace: Towards Ultimate Fairness via MixFair Adapter in Face Recognition
Fu-En Wang, Chien-Yi Wang, Min Sun +1
Although significant progress has been made in face recognition, demographic bias still exists in face recognition systems. For instance, it usually happens that the face recogniti…
Holistic Interaction Transformer Network for Action Detection
Gueter Josmy Faure, Min-Hung Chen, Shang-Hong Lai
Actions are about how we interact with the environment, including other people, objects, and ourselves. In this paper, we propose a novel multi-modal Holistic Interaction Transform…
Extremely Low-light Image Enhancement with Scene Text Restoration
Pohao Hsu, Che-Tsung Lin, Chun Chet Ng +5
Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. However, w…
Local-Adaptive Face Recognition via Graph-based Meta-Clustering and Regularized Adaptation
Wenbin Zhu, Chien-Yi Wang, Kuan-Lun Tseng +2
Due to the rising concern of data privacy, it's reasonable to assume the local client data can't be transferred to a centralized server, nor their associated identity label is prov…
PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition
Chien-Yi Wang, Yu-Ding Lu, Shang-Ta Yang +1
Face anti-spoofing (FAS) plays a critical role in securing face recognition systems from different presentation attacks. Previous works leverage auxiliary pixel-level supervision a…
High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network
Meng-Tzu Chiu, Hsun-Ying Cheng, Chien-Yi Wang +1
Deep learning approaches have achieved highly accurate face recognition by training the models with very large face image datasets. Unlike the availability of large 2D face image d…
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition
Chih-Ting Liu, Chien-Yi Wang, Shao-Yi Chien +1
Current state-of-the-art deep learning based face recognition (FR) models require a large number of face identities for central training. However, due to the growing privacy awaren…
Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing
Yu-Chun Wang, Chien-Yi Wang, Shang-Hong Lai
As face recognition is widely used in diverse security-critical applications, the study of face anti-spoofing (FAS) has attracted more and more attention. Several FAS methods have…
ByeGlassesGAN: Identity Preserving Eyeglasses Removal for Face Images
Yu-Hui Lee, Shang-Hong Lai
In this paper, we propose a novel image-to-image GAN framework for eyeglasses removal, called ByeGlassesGAN, which is used to automatically detect the position of eyeglasses and th…
Unified Representation Learning for Cross Model Compatibility
Chien-Yi Wang, Ya-Liang Chang, Shang-Ta Yang +2
We propose a unified representation learning framework to address the Cross Model Compatibility (CMC) problem in the context of visual search applications. Cross compatibility betw…