no code implementations • ICCV 2023 • Zhengfeng Lai, Noranart Vesdapunt, Ning Zhou, Jun Wu, Cong Phuoc Huynh, Xuelu Li, Kah Kuen Fu, Chen-Nee Chuah
We then utilize CLIP's zero-shot prediction to formulate a Pseudo-labeling setting with Adaptive Debiasing in CLIP (PADCLIP) by adjusting causal inference with our momentum and CFM.
Ranked #3 on Unsupervised Domain Adaptation on DomainNet
no code implementations • CVPR 2021 • Noranart Vesdapunt, Baoyuan Wang
Our confidence ranker is model-agnostic, so we can augment the data by choosing the pairs from multiple face detectors during the training, and generalize to a wide range of face detectors during the testing.
no code implementations • ECCV 2020 • Bindita Chaudhuri, Noranart Vesdapunt, Linda Shapiro, Baoyuan Wang
Traditional methods for image-based 3D face reconstruction and facial motion retargeting fit a 3D morphable model (3DMM) to the face, which has limited modeling capacity and fail to generalize well to in-the-wild data.
no code implementations • ECCV 2020 • Noranart Vesdapunt, Mitch Rundle, HsiangTao Wu, Baoyuan Wang
In this paper, we introduce a novel approach to learn a 3D face model using a joint-based face rig and a neural skinning network.
no code implementations • CVPR 2019 • Bindita Chaudhuri, Noranart Vesdapunt, Baoyuan Wang
Facial motion retargeting is an important problem in both computer graphics and vision, which involves capturing the performance of a human face and transferring it to another 3D character.
no code implementations • 28 Mar 2018 • Noranart Vesdapunt, Nongluk Covavisaruch
The selected segmentation techniques have been validated by accuracy, sensitivity, and specificity using leave-one-out cross-validation to determine the possibility of each techniques first then maximizes the accuracy from the training set.
no code implementations • 20 Mar 2018 • Baoyuan Wang, Noranart Vesdapunt, Utkarsh Sinha, Lei Zhang
The system is designed to run in the viewfinder mode and capture a burst sequence of frames before and after the shutter is pressed.
no code implementations • 6 Mar 2018 • Huan Yang, Baoyuan Wang, Noranart Vesdapunt, Minyi Guo, Sing Bing Kang
We propose a reinforcement learning approach for real-time exposure control of a mobile camera that is personalizable.
no code implementations • 1 Dec 2016 • Jonathan Shen, Noranart Vesdapunt, Vishnu N. Boddeti, Kris M. Kitani
It has been observed that many of the parameters of a large network are redundant, allowing for the possibility of learning a smaller network that mimics the outputs of the large network through a process called Knowledge Distillation.
no code implementations • 2 May 2016 • Noranart Vesdapunt, Utkarsh Sinha
In this paper, we assumed slightly uniform change of velocity between two nearby frames, and solve the optical flow problem by traditional method, Lucas-Kanade(1981).