155 citations · 331 across the 17 of their papers we have counts for
17 papers
Domain Generalization via Balancing Training Difficulty and Model Capability
Xueying Jiang, Jiaxing Huang, Sheng Jin +1
Domain generalization (DG) aims to learn domain-generalizable models from one or multiple source domains that can perform well in unseen target domains. Despite its recent progress…
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin Memory
Jingyi Zhang, Jiaxing Huang, Xueying Jiang +1
Black-box unsupervised domain adaptation (UDA) learns with source predictions of target data without accessing either source data or source models during training, and it has clear…
Prompt Ensemble Self-training for Open-Vocabulary Domain Adaptation
Jiaxing Huang, Jingyi Zhang, Han Qiu +2
Traditional domain adaptation assumes the same vocabulary across source and target domains, which often struggles with limited transfer flexibility and efficiency while handling ta…
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds
Aoran Xiao, Jiaxing Huang, Weihao Xuan +6
Robust point cloud parsing under all-weather conditions is crucial to level-5 autonomy in autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) mode…
Vision-Language Models for Vision Tasks: A Survey
Jingyi Zhang, Jiaxing Huang, Sheng Jin +1
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, l…
Contextual Text Block Detection towards Scene Text Understanding
Chuhui Xue, Jiaxing Huang, Shijian Lu +2
Most existing scene text detectors focus on detecting characters or words that only capture partial text messages due to missing contextual information. For a better understanding…
Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion
Gongjie Zhang, Zhipeng Luo, Jiaxing Huang +2
The recently proposed DEtection TRansformer (DETR) has established a fully end-to-end paradigm for object detection. However, DETR suffers from slow training convergence, which hin…
UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer via Hierarchical Mask Calibration
Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang +1
Domain adaptive panoptic segmentation aims to mitigate data annotation challenge by leveraging off-the-shelf annotated data in one or multiple related source domains. However, exis…
Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentation
Dayan Guan, Jiaxing Huang, Aoran Xiao +1
Semi-supervised semantic segmentation learns from small amounts of labelled images and large amounts of unlabelled images, which has witnessed impressive progress with the recent a…
Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey
Aoran Xiao, Jiaxing Huang, Dayan Guan +3
Point cloud data have been widely explored due to its superior accuracy and robustness under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved very i…
I2C2W: Image-to-Character-to-Word Transformers for Accurate Scene Text Recognition
Chuhui Xue, Jiaxing Huang, Wenqing Zhang +3
Leveraging the advances of natural language processing, most recent scene text recognizers adopt an encoder-decoder architecture where text images are first converted to representa…
Cross-View Regularization for Domain Adaptive Panoptic Segmentation
Jiaxing Huang, Dayan Guan, Aoran Xiao +1
Panoptic segmentation unifies semantic segmentation and instance segmentation which has been attracting increasing attention in recent years. However, most existing research was co…
FSDR: Frequency Space Domain Randomization for Domain Generalization
Jiaxing Huang, Dayan Guan, Aoran Xiao +1
Domain generalization aims to learn a generalizable model from a known source domain for various unknown target domains. It has been studied widely by domain randomization that tra…
DA-DETR: Domain Adaptive Detection Transformer with Information Fusion
Jingyi Zhang, Jiaxing Huang, Zhipeng Luo +3
The recent detection transformer (DETR) simplifies the object detection pipeline by removing hand-crafted designs and hyperparameters as employed in conventional two-stage object d…
FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation
Aoran Xiao, Xiaofei Yang, Shijian Lu +2
Scene understanding based on LiDAR point cloud is an essential task for autonomous cars to drive safely, which often employs spherical projection to map 3D point cloud into multi-c…
Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection
Dayan Guan, Jiaxing Huang, Aoran Xiao +2
Unsupervised domain adaptive object detection aims to adapt detectors from a labelled source domain to an unlabelled target domain. Most existing works take a two-stage strategy th…
Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation
Jiaxing Huang, Shijian Lu, Dayan Guan +1
Recent advances in unsupervised domain adaptation for semantic segmentation have shown great potentials to relieve the demand of expensive per-pixel annotations. However, most exis…