对于Open World Object Detection任务最重要一点就是可以学习新的类别,而过去有很多工作表明学习新的类别会遗忘之前的类别。在解决该问题方面,有大量工作证明相比于复杂的方案,一个有效的(贪婪的)example replay策略往往能得到SOTA表现,并且在few-shot object detection中也证明了存储少量样本和replay的有效性 基于上述前...
The effectiveness of storing few examples and replaying has been found effective in the re- lated few-shot object detection setting by Wang et al. [62]. These motivates us to use a relatively simple methodology for ORE to mitigate forgetting i.e., we store a balanced set of exemplars and...
Vision-Language Open-world Recognition, Object Detection, and Visual Grounding 报告时间 2023-08-30 00:00 报告地点 线上 主办方 中国图象图形学学会、CSIG女科技工作者委员会 报告摘要 近期,视觉语言预训练模型如CLIP和多模态预训练基础大模型GPT4等在不同的视觉识别和视觉语言多模态任务下取得突破,但如何利用...
Open World Object Detection (OWOD) is a challenging computer vision problem that requires detecting unknown objects and gradually learning the identified unknown classes. However, it cannot distinguish unknown instances as multiple unknown classes. In th
发表OpenNRE的论文,论文详细说明了OpenNRE的各个组件。 OpenNRE的github的地址。 清华整理的做关系抽取必读的文章的地址。 OpenNRE实现了基于sentence-level,bag-level和few-shot的relation extraction(关系抽取)。bag-level的关系抽取也就是基于远程监督的关系抽取。 OpenNRE的结构 OpenNRE主要包括Tok... ...
Order: Open world object detection on road scenes. In Proc. NeurIPS Work- shops, 2021. 1, 2 [29] Kuan-Chieh Wang, Paul Vicol, Eleni Triantafillou, and Richard Zemel. Few-shot out-of-distribution detection. In- ternational Conference on Machine Learning (ICML) Work- shop on Un...
Towards Open-World Object-Based Anomaly Detection viaSelf-Supervised Outlier Synthesis Object detection is a pivotal task in computer vision that has received significant attention in previous years. Nonetheless, the capability of a detector ... BKS Isaac-Medina,YFA Gaus,N Bhowmik,... - European ...
(2)从任务出发,实体分割具有很强的泛化能力进行无类别的全图分割,这或许有很强的潜力去做有类别的识别任务,例如全景分割,few shot或者长尾分布的分割。Mask都已分好,识别是不是也会变得容易很多?目前我们也在基于这个结构对全景分割进行尝试,PQ指标也几乎和PanopticFCN持平。因此实体分割也可以做为pretrain的模型承担...
LP-OVOD: Open-Vocabulary Object Detection by Linear Probing (WACV 2024) [paper] [code] Meta-Adapter: An Online Few-shot Learner for Vision-Language Model (NeurIPS 2023) [paper] Open-Vocabulary Object Detection with Meta Prompt Representation and Instance Contrastive Optimization (BMVC 2023) [...
Zero-Shot Open Set Detection by Extending CLIP. Sepideh Esmaeilpour, Bing Liu, Eric Robertson, Lei Shu. (ArXiv 2021). Adversarial Reciprocal Points Learning for Open Set Recognition. Guangyao Chen, Peixi Peng, Xiangqian Wang, Yonghong Tian. (TPAMI 2021).[code]. ...