no code implementations • 13 Apr 2024 • Bor-Shiun Wang, Chien-Yi Wang, Wei-Chen Chiu
Addressing this gap, we introduce the Multi-Level Concept Prototypes Classifier (MCPNet), an inherently interpretable model.
4 code implementations • 14 Feb 2024 • Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin, Pavlo Molchanov, Yu-Chiang Frank Wang, Kwang-Ting Cheng, Min-Hung Chen
By employing DoRA, we enhance both the learning capacity and training stability of LoRA while avoiding any additional inference overhead.
no code implementations • 22 Jan 2024 • Ci-Siang Lin, Chien-Yi Wang, Yu-Chiang Frank Wang, Min-Hung Chen
In this way, SemPLeS can perform better semantic alignment between object regions and the associated class labels, resulting in desired pseudo masks for training the segmentation model.
2 code implementations • 26 Sep 2023 • Hsu-kuang Chiu, Chien-Yi Wang, Min-Hung Chen, Stephen F. Smith
However, their proposed methods mainly use cooperative detection results as input to a standard single-sensor Kalman Filter-based tracking algorithm.
no code implementations • ICCV 2023 • Fu-En Yang, Chien-Yi Wang, Yu-Chiang Frank Wang
To leverage robust representations from large-scale models while enabling efficient model personalization for heterogeneous clients, we propose a novel personalized FL framework of client-specific Prompt Generation (pFedPG), which learns to deploy a personalized prompt generator at the server for producing client-specific visual prompts that efficiently adapts frozen backbones to local data distributions.
1 code implementation • 30 Jun 2023 • Hsi-Che Lin, Chien-Yi Wang, Min-Hung Chen, Szu-Wei Fu, Yu-Chiang Frank Wang
This technical report describes our QuAVF@NTU-NVIDIA submission to the Ego4D Talking to Me (TTM) Challenge 2023.
no code implementations • 25 Jun 2023 • Chih-Jung Chang, Yaw-Chern Lee, Shih-Hsuan Yao, Min-Hung Chen, Chien-Yi Wang, Shang-Hong Lai, Trista Pei-Chun Chen
Face anti-spoofing (FAS) is indispensable for a face recognition system.
no code implementations • 10 Apr 2023 • Weng-Tai Su, Min-Hung Chen, Chien-Yi Wang, Shang-Hong Lai, Trista Pei-Chun Chen
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem.
no code implementations • 29 Nov 2022 • 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.
1 code implementation • 28 Nov 2022 • Fu-En Wang, Chien-Yi Wang, Min Sun, Shang-Hong Lai
In this paper, we propose MixFairFace framework to improve the fairness in face recognition models.
no code implementations • CVPR 2022 • Wenbin Zhu, Chien-Yi Wang, Kuan-Lun Tseng, Shang-Hong Lai, Baoyuan Wang
Leveraging the environment-specific local data after the deployment of the initial global model, LaFR aims at getting optimal performance by training local-adapted models automatically and un-supervisely, as opposed to fixing their initial global model.
3 code implementations • CVPR 2022 • Chien-Yi Wang, Yu-Ding Lu, Shang-Ta Yang, Shang-Hong Lai
Previous works leverage auxiliary pixel-level supervision and domain generalization approaches to address unseen spoof types.
1 code implementation • 23 Dec 2021 • Chih-Ting Liu, Chien-Yi Wang, Shao-Yi Chien, Shang-Hong Lai
Current state-of-the-art deep learning based face recognition (FR) models require a large number of face identities for central training.
no code implementations • 22 Dec 2021 • Meng-Tzu Chiu, Hsun-Ying Cheng, Chien-Yi Wang, Shang-Hong Lai
Our DepthNet is used to augment a large 2D face image dataset to a large RGB-D face dataset, which is used for training an accurate RGB-D face recognition model.
no code implementations • 18 Oct 2021 • Yu-Chun Wang, Chien-Yi Wang, Shang-Hong Lai
Unlike previous FAS disentanglement works with one-stage architecture, we found that the dual-stage training design can improve the training stability and effectively encode the features to detect unseen attack types.
no code implementations • 11 Aug 2020 • Chien-Yi Wang, Ya-Liang Chang, Shang-Ta Yang, Dong Chen, Shang-Hong Lai
We propose a unified representation learning framework to address the Cross Model Compatibility (CMC) problem in the context of visual search applications.
1 code implementation • ICCV 2015 • Xiang Fu, Chien-Yi Wang, Chen Chen, Changhu Wang, C. -C. Jay Kuo
The contour-guided color palette (CCP) is proposed for robust image segmentation.