To address these issues, we propose SSLAD, a S elf- S upervised L earning approach especially suited for object detection in the context of A utonomous D riving. SSLAD computes local image descriptors that are
作者将数据集分为四种,分别是:全检测框 / 漏选一个检测框 / 漏选一般检测框 / 只保留一个检测框 消融实验 第一行为原图检测的分支,第二行为增强图检测的分支 论文信息 Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection ojs.aaai.org/index.php/ 发布于 2021-09-17 12:05 ...
利用自监督表示学习(Self-Supervised Representation Learning,SSL)来设计两个前置任务:跨模态自动编码器 和深度轮廓估计。本文的前置任务只需要 少量未标记 的RGB-D 数据集来执行预训练,这使得网络能够捕获丰富的语义上下文信息,同时减少两种模态之间的差距,从而为下游任务提供有效的初始化。 采用一致性-差异聚合(Consiste...
Self-supervised learning for 3D object retrieval has been studied in the past, but only limited work has compared self-supervised learning to supervised learning in an extensive manner. Within this small subset of works, we argue that various aspects could be improved. First of all, self-supervi...
Self-Supervised Learning 尽管不需要手动注释,但非监督数据具有丰富的结构信息,可以通过自我监督学习,即隐藏数据信息的一个子部分,然后试图恢复它。 这个过程通常被表示为伪装任务,可能的例子有图像补全[31]、着色[32]、[33]、补丁[34]、[35]、旋转识别[36]等等。 自我监督学习已经被广泛用于几乎没有注释的监督学...
Keywords: contrastive learning; self-supervised learning; discriminative(有区别的) learning; image/video classification; object detection; unsupervised learning; transfer learning 翻译:自监督学习因为它可以避免给大规模数据做标注的成本而获得普及。它有能力采用自定义的伪标签做监督并使用学习好的模型表示几个下游...
seeing any experimental data or real object features, GedankenNet also implicitly acquired the physical information of wave propagation in free space and gained robustness towards defocused holograms or changes in the pixel size through the same self-supervised learning process. Furthermore, for phase-...
SSL can create generalist models that can be fine-tuned for many downstream tasks without large-scale labeled datasets. Self-supervised learning was first popularized in the field of natural language processing (NLP) when researchers leveraged copious amounts of unlabeled text scraped from the internet...
Self-supervised Representation Learning for the Object Detection of Marine Radar One of the main challenges in object detection tasks is to detect the small and messy targets in complex backgrounds. For the marine radar images, this cha... L Si,G Li,C Zheng,... - 《Proceedings of Internatio...
Self-Supervised Learning 尽管不需要手动注释,但非监督数据具有丰富的结构信息,可以通过自我监督学习,即隐藏数据信息的一个子部分,然后试图恢复它。 这个过程通常被表示为伪装任务,可能的例子有图像补全[31]、着色[32]、[33]、补丁[34]、[35]、旋转识别[36]等等。 自我监督学习已经被广泛用于几乎没有注释的监督学...