MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection 单位:中科院 代码:https://github.com/BraveGroup/PointSAM-for-MixSup 论文:https://arxiv.org/abs/2401.16305 CVPR 2023 论文和开源项目合集请戳—>https://github.com/amusi/CVPR2023-Papers-with-Code ICCV 2023 论文...
4.1 MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data 5 分布外检测 5.1 DOS: Diverse Outlier Sampling for Out-of-Distribution Detection 简单整理罗列了一波ICLR 2024中的异常检测论文。大致划分为五个研究方向:工业异常、图异常、扩散模型、表格数据异常、OoD检测。论文代码链接和摘要机翻汇总如下...
为了改进 CLIP 模型,来自浙江大学、新加坡管理大学、哈佛大学的研究者联合提出 AnomalyCLIP,使其能在不同领域中更准确地进行零样本异常检测。AnomalyCLIP 的核心思想是学习一种与对象不相关的文本提示技术(object-agnostic learning),这种技术...
基线选择:我们将所提出的ReSimAD与三种典型的跨域基线进行比较:a)直接使用仿真引擎进行数据仿真的基线;b)通过改变仿真引擎中的传感器参数设置,来进行数据仿真的基线;c)域自适应(UDA)基线. 度量标准:我们对齐目前进行3D cross-domain object detection的评价标准,分别采用基于BEV的和基于3D的AP作为评价度量标准。 参数设...
[10] Charles R Qi, Or Litany, Kaiming He, and Leonidas J Guibas. Deep hough voting for 3d object detection in point clouds. In International Conference on Computer Vision (ICCV), 2019. [11] Yixin Zhu, Tao Gao, Lifeng Fan, Siyuan Huang, Mark Edmonds, Hangxin Liu, Feng Gao, Chi Zhang...
12.Fusion is Not Enough: Single Modal Attack on Fusion Models for 3D Object Detection 13.Transformer Fusion with Optimal Transport 14.Parameter-Efficient Multi-Task Model Fusion with Partial Linearizeation 15.Jointly Training Large Autoregressive Multimodal Models ...
论文名称:AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection 文章地址:https://arxiv.org/pdf/2310.18961.pdf 代码地址:https://github.com/zqhang/AnomalyCLIP 背景 传统的异常检测方法通常需要在特定应用领域内有可用的训练样本来学习检测模型。然而,在某些情况下,这个假设可能并不成立,...
论文链接: https://openreview.net/pdf?id=VNqaB1g9393 代码链接: https://github.com/thuml/Transfer-Learning-Library/tree/dev-tllib/examples/domain_adaptation/object_detection 了解基本的域对抗自适应算法可以帮助你更好地阅读本文。相关文章: https://zhuanlan.zhihu.com/p/466811491/ ...
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection Yichao Shen, Zigang Geng,Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng,Baining Guo ICLR 2024| August 2023 DOIPDF Weakly-supervised Audio Separation via Bi-modal Semantic Similarity ...
论文题目:AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection 论文链接: https://arxiv.org/pdf/2310.18961.pdf 代码链接: https://github.com/zqhang/AnomalyCLIP 1、背景 传统的异常检测方法通常需要在特定应用领域内有可用的训练样本来学习检测模型。然而,在某些情况下,这个假设可能并...