Aiming to detect novel objects from only a few annotated samples, few-shot object detection (FSOD) has undergone remarkable development. Previous works rarely pay attention to the perspective of gradient propagation to optimize existing methods, therefore failing to make full use of information for ...
CVLAB-Unibo/Real-time-self-adaptive-deep-stereo Star420 Code Issues Pull requests Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL) tensorflowstereo-visionpretrained-weightsunsupervised-machine-learningdomain-adaptationdispnetonline-adaptationmadnetcvpr2019cvpr2019-oraldeep-stereo-network ...
首先介绍一个跨域小样本学习任务(Cross-Domain Few-Shot Learning,CD-FSL), CD-FSL解决的是源域与目标域存在领域差异情况下的小样本学习任务,即集合了小样本学习与跨域两个任务的难点问题:1)源域S与目标域T类别集合完全不同,且目标域T中的类别仅存在少量标注样本,例如1shot,5shot;2)S与T属于两个不同领域,例...
Domain-adaptive graph neural network for few-shot learning few-shot classification (FSC) is to build a model to discriminate novel categories that do not present in training categories with limited labeled samples... Z Yang,W Li,T Zheng,... - Knowledge-Based Systems 被引量: 0发表: 2023年 ...
Domain Adaptive Based Semantic Segmentation semantic-segmentationdomainadaptationunet-pytorchunet-segmentationcropandweed UpdatedMay 30, 2024 Python Complexity metric for broadscale domain adaptation and adaptive sampling. machine-learningcomplexityresearch-projectdomainadaptationuniversity-of-houston ...
Domain adaptationis to achieve the effect that the performance of the model in another domain approximates or even remains in the original domain. Alirezazadeh et al. [167] suggested a new unsupervised adaptive technique for classifying breasthistopathologyimages based onrepresentation learning. This me...
While transformer-based open-set detectors, such as DE-ViT, show promise in traditional few-shot object detection, their generalization to CD-FSOD remains unclear: 1) can such open-set detection methods easily generalize to CD-FSOD? 2) If not, how can models be enhanced when facing huge ...
This paper studies the challenging cross-domain few-shot object detection (CD-FSOD), aiming to develop an accurate object detector for novel domains with minimal labeled examples. While transformer-based open-set detectors, such as DE-ViT, show promise in traditional few-shot object detection, the...
首先介绍一个跨域小样本学习任务(Cross-Domain Few-Shot Learning,CD-FSL), CD-FSL解决的是源域与目标域存在领域差异情况下的小样本学习任务,即集合了小样本学习与跨域两个任务的难点问题:1)源域S与目标域T类别集合完全不同,且目标域T中的类别仅存在少量标注样本,例如1shot,5shot;2)S与T属于两个不同领域,例...
NeurIPS'23 When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation [paper] Source-free domain adaptation using visual prompt tuning Updated at 2024-01-08: NeurIPS'23 CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation [arxiv] ...