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

Showing 151175 of 449 papers

TitleStatusHype
DreamHOI: Subject-Driven Generation of 3D Human-Object Interactions with Diffusion Priors0
Compositional 3D Human-Object Neural Animation0
DPMix: Mixture of Depth and Point Cloud Video Experts for 4D Action Segmentation0
Do Deep Neural Networks Model Nonlinear Compositionality in the Neural Representation of Human-Object Interactions?0
Complex Video Action Reasoning via Learnable Markov Logic Network0
Distillation Using Oracle Queries for Transformer-Based Human-Object Interaction Detection0
Distillation of Human-Object Interaction Contexts for Action Recognition0
AvatarGO: Zero-shot 4D Human-Object Interaction Generation and Animation0
An Abstract Specification of VoxML as an Annotation Language0
Amplifying Key Cues for Human-Object-Interaction Detection0
COBE: Contextualized Object Embeddings from Narrated Instructional Video0
CL-HOI: Cross-Level Human-Object Interaction Distillation from Vision Large Language Models0
Disentangled Interaction Representation for One-Stage Human-Object Interaction Detection0
Autonomous Character-Scene Interaction Synthesis from Text Instruction0
Discovering Syntactic Interaction Clues for Human-Object Interaction Detection0
Classifying All Interacting Pairs in a Single Shot0
Discovering Human Interactions With Large-Vocabulary Objects via Query and Multi-Scale Detection0
CinePile: A Long Video Question Answering Dataset and Benchmark0
HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objects0
HODN: Disentangling Human-Object Feature for HOI Detection0
HOIAnimator: Generating Text-prompt Human-object Animations using Novel Perceptive Diffusion Models0
Discovering Human Interactions in Videos with Limited Data Labeling0
CHORUS : Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images0
Diffgrasp: Whole-Body Grasping Synthesis Guided by Object Motion Using a Diffusion Model0
CHORUS: Learning Canonicalized 3D Human-Object Spatial Relations from Unbounded Synthesized Images0
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Benchmark Results

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