SOTAVerified

Human-Object Interaction Detection

Human-Object Interaction (HOI) detection is a task of identifying "a set of interactions" in an image, which involves the i) localization of the subject (i.e., humans) and target (i.e., objects) of interaction, and ii) the classification of the interaction labels.

Papers

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Showing 401–449 of 449 papers

TitleStatusHype
Pose-aware Multi-level Feature Network for Human Object Interaction DetectionCode0
Comparative Analysis of CNN-based Spatiotemporal Reasoning in VideosCode0
Reasoning About Human-Object Interactions Through Dual Attention Networks—0
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense—0
Semantics to Space(S2S): Embedding semantics into spatial space for zero-shot verb-object query inferencing—0
Grounded Human-Object Interaction Hotspots from Video (Extended Abstract)—0
Learning to Detect Human-Object Interactions With Knowledge—0
HAKE: Human Activity Knowledge EngineCode1
Multi-View Region Adaptive Multi-temporal DMM and RGB Action Recognition—0
Recurrent Space-time Graph Neural NetworksCode0
Detecting Human-Object Interactions via Functional Generalization—0
Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions?—0
Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation—0
Grounded Human-Object Interaction Hotspots from VideoCode0
Transferable Interactiveness Knowledge for Human-Object Interaction DetectionCode1
No-Frills Human-Object Interaction Detection: Factorization, Layout Encodings, and Training TechniquesCode0
Compositional Learning for Human Object Interaction—0
iCAN: Instance-Centric Attention Network for Human-Object Interaction DetectionCode1
Interact as You Intend: Intention-Driven Human-Object Interaction Detection—0
Learning Human-Object Interactions by Graph Parsing Neural NetworksCode0
Pairwise Body-Part Attention for Recognizing Human-Object InteractionsCode0
iMapper: Interaction-guided Joint Scene and Human Motion Mapping from Monocular Videos—0
Pose-Based Two-Stream Relational Networks for Action Recognition in Videos—0
Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning—0
Temporal Relational Reasoning in VideosCode0
Simultaneous Joint and Object Trajectory Templates for Human Activity Recognition from 3-D Data—0
Attentional Pooling for Action RecognitionCode0
Deep Semantic Abstractions of Everyday Human Activities: On Commonsense Representations of Human Interactions—0
A self-organizing neural network architecture for learning human-object interactions—0
Learning event representation: As sparse as possible, but not sparser—0
Learning Action Recognition Model From Depth and Skeleton Videos—0
Fine-grained Event Learning of Human-Object Interaction with LSTM-CRF—0
Care about you: towards large-scale human-centric visual relationship detection—0
Detecting and Recognizing Human-Object Interactions—0
Recurrent Models for Situation Recognition—0
Learning to Detect Human-Object Interactions—0
Jointly learning heterogeneous features for rgb-d activity recognition—0
Beyond Holistic Object Recognition: Enriching Image Understanding with Part States—0
Human Centred Object Co-Segmentation—0
Low-Cost Scene Modeling using a Density Function Improves Segmentation Performance—0
Weakly Supervised Learning of Affordances—0
Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering—0
First Person Action-Object Detection with EgoNet—0
HICO: A Benchmark for Recognizing Human-Object Interactions in Images—0
Interaction Part Mining: A Mid-Level Approach for Fine-Grained Action Recognition—0
Object Modelling with a Handheld RGB-D Camera—0
Contextual Action Recognition with R*CNNCode0
Discovering Human Interactions in Videos with Limited Data Labeling—0
TUHOI: Trento Universal Human Object Interaction Dataset—0
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All datasetsHICO-DETV-COCOHICOVidHOIAmbiguious-HOIMECCANO

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Ours (PViC+)mAP46.49—Unverified
2RLIPv2 (Swin-L)mAP45.09—Unverified
3PViC-SwinLmAP44.32—Unverified
4SOV-STG (Swin-L)mAP43.35—Unverified
5DiffHOImAP41.5—Unverified
6ViPLOmAP37.22—Unverified
7FGAHOImAP37.18—Unverified
8ERNetmAP36.89—Unverified
9CQL+GEN-VLKT-LmAP36.03—Unverified
10QAHOI (Swin-L)mAP35.78—Unverified
#ModelMetricClaimedVerifiedStatus
1RLIPv2AP(S1)72.1—Unverified
2MURENAP(S1)68.8—Unverified
3STIPAP(S1)66—Unverified
4DiffHOIAP(S1)65.7—Unverified
5OCN (ResNet101)AP(S1)65.3—Unverified
6OCN (ResNet50)AP(S1)64.2—Unverified
7CDN (ResNet101)AP(S1)63.91—Unverified
8HOICLIPAP(S1)63.5—Unverified
9QPIC + CPCMAP63.1—Unverified
10Body Part InteractivenessAP(S1)63—Unverified
#ModelMetricClaimedVerifiedStatus
1DEFRmAP65.6—Unverified
2HAKEmAP47.1—Unverified
3PaStaNetmAP46.3—Unverified
4RelViTmAP43.98—Unverified
5Pairwise-PartmAP39.9—Unverified
6Mallya & LazebnikmAP36.1—Unverified
7Girdhar & RamananmAP34.6—Unverified
8R*CNNmAP28.5—Unverified
#ModelMetricClaimedVerifiedStatus
1HOI4ABOTDetection: Full (mAP@0.5)11.12—Unverified
2ST-GAZEDetection: Full (mAP@0.5)10.4—Unverified
3STTRANDetection: Full (mAP@0.5)7.61—Unverified
#ModelMetricClaimedVerifiedStatus
1DJ-RNmAP10.37—Unverified
2iCANmAP8.14—Unverified
#ModelMetricClaimedVerifiedStatus
1SlowFast + FasterRCNNmAP@0.5 role25.93—Unverified