36 citations · 49 across the 9 of their papers we have counts for
9 papers · 1 filter
HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing
Ivannia Gomez Moreno, Yi Yao, Ye Tian +7
LiDAR semantic segmentation plays a pivotal role in 3D scene understanding for edge applications such as autonomous driving. However, significant challenges remain for real-world d…
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…
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…
Domain Adaptive Scene Text Detection via Subcategorization
Zichen Tian, Chuhui Xue, Jingyi Zhang +1
Most existing scene text detectors require large-scale training data which cannot scale well due to two major factors: 1) scene text images often have domain-specific distributions…
Towards Efficient Use of Multi-Scale Features in Transformer-Based Object Detectors
Gongjie Zhang, Zhipeng Luo, Zichen Tian +3
Multi-scale features have been proven highly effective for object detection but often come with huge and even prohibitive extra computation costs, especially for the recent Transfo…
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…
Spectral Unsupervised Domain Adaptation for Visual Recognition
Jingyi Zhang, Jiaxing Huang, Zichen Tian +1
Though unsupervised domain adaptation (UDA) has achieved very impressive progress recently, it remains a great challenge due to missing target annotations and the rich discrepancy…
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…