8 citations · 18 across the 6 of their papers we have counts for
6 papers
Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams
Ziqiang Wang, Zhixiang Chi, Yanan Wu +4
Given a model trained on source data, Test-Time Adaptation (TTA) enables adaptation and inference in test data streams with domain shifts from the source. Current methods predomina…
Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization
Yanan Wu, Zhixiang Chi, Yang Wang +2
Test-time domain adaptation aims to adapt the model trained on source domains to unseen target domains using a few unlabeled images. Emerging research has shown that the label and…
Hyper-Skin: A Hyperspectral Dataset for Reconstructing Facial Skin-Spectra from RGB Images
Pai Chet Ng, Zhixiang Chi, Yannick Verdie +2
We introduce Hyper-Skin, a hyperspectral dataset covering wide range of wavelengths from visible (VIS) spectrum (400nm - 700nm) to near-infrared (NIR) spectrum (700nm - 1000nm), un…
MetaGCD: Learning to Continually Learn in Generalized Category Discovery
Yanan Wu, Zhixiang Chi, Yang Wang +1
In this paper, we consider a real-world scenario where a model that is trained on pre-defined classes continually encounters unlabeled data that contains both known and novel class…
Error-Aware Spatial Ensembles for Video Frame Interpolation
Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu +4
Video frame interpolation~(VFI) algorithms have improved considerably in recent years due to unprecedented progress in both data-driven algorithms and their implementations. Recent…
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay
Huan Liu, Li Gu, Zhixiang Chi +4
Few-shot class-incremental learning (FSCIL) has been proposed aiming to enable a deep learning system to incrementally learn new classes with limited data. Recently, a pioneer clai…