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2023年3月28日 · Abstract: Human-Object Interaction (HOI) detection aims to localize human-object pairs and recognize their interactions. Recently, Contrastive Language-Image Pre-training (CLIP) has shown great potential in providing interaction prior for …

Proposed by TIN (TPAMI version, Transferable Interactiveness Network). It is built on HAKE data, includes 110K+ images and 520 HOIs (without the 80 "no_interaction" HOIs of HICO-DET to avoid the incomplete labeling). It has a more severe …

2023年7月26日 · CVPR 2023 Accepted Paper HOICLIP: Efficient Knowledge Transfer for HOI Detection with Vision-Language Models Resources

2020年3月29日 · Our HOI-A dataset is built upon our HOI-W dataset for the ICCV HOI detection challenge with some refinements and extensions. Renaming the HOI-W as HOI-A because we find our dataset is not really "in the wild" due to the limited object/verb categories, and "for application" is more suitable.

2017年2月17日 · We study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects.

2023年8月13日 · 创建了一个新的视频HOI的benchmark（VidHOI），并介绍了以关键帧为中心的检测策略。 提出了时空baseline的ST-HOI，挖掘了基于轨迹的时间特征（correctly-localized visual features、spatial-temporal masking pose features和轨迹特征）

Human and Object stream：提取human和object的特征并且分类（类别数为HOI classes） Pairwise Stream ：给定human-object proposal，提取人与物位置关系的feature。 本文提出利用 Interaction Patterns 去encode两bboxes的relative location。

本文的出发点是使用可学习的query机制代替传统检测任务中的区域提议框（region proposals），提出了一种新颖的两阶段 Unary-Pairwise Transformer，本文的实验在 HICO-DET 和 V-COCO 两个权威数据集上进行，实验结果已达SOTA，此外，整体框架在两阶段的设置下仍然能在推理阶段达到实时性能。 人-物交互检测（HOI）任务需要在定位到图像中人物和交互目标的同时 对交互动作进行识别和分类。 目前的技术路线主要有两种，分别是单阶段检测器和两阶段 …

In this paper, we reformulate HOI detection as an adaptive set prediction problem, with this novel formulation, we propose an Adaptive Set-based one-stage framework (AS-Net) with parallel instance and interaction branches. To attain this, we map a trainable interaction query set to an interaction prediction set with transformer.