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Found 31 papers, 22 papers with code
Primitive-based 3D Human-Object Interaction Modelling and Programming
To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images.
Revisit Human-Scene Interaction via Space Occupancy
Human-scene Interaction (HSI) generation is a challenging task and crucial for various downstream tasks.
Dancing with Still Images: Video Distillation via Static-Dynamic Disentanglement
It first distills the videos into still images as static memory and then compensates the dynamic and motion information with a learnable dynamic memory block.
Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning
One possible path of activity reasoning is building a symbolic system composed of symbols and rules, where one rule connects multiple symbols, implying human knowledge and reasoning abilities.
Bridging the Gap between Human Motion and Action Semantics via Kinematic Phrases
The goal of motion understanding is to establish a reliable mapping between motion and action semantics, while it is a challenging many-to-many problem.
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding
With the surge in attention to Egocentric Hand-Object Interaction (Ego-HOI), large-scale datasets such as Ego4D and EPIC-KITCHENS have been proposed.
Distill Gold from Massive Ores: Efficient Dataset Distillation via Critical Samples Selection
Our method consistently enhances the distillation algorithms, even on much larger-scale and more heterogeneous datasets, e. g. ImageNet-1K and Kinetics-400.
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding
By aligning the classes of previous datasets to our semantic space, we gather (image/video/skeleton/MoCap) datasets into a unified database in a unified label system, i. e., bridging "isolated islands" into a "Pangea".
Beyond Object Recognition: A New Benchmark towards Object Concept Learning
To support OCL, we build a densely annotated knowledge base including extensive labels for three levels of object concept (category, attribute, affordance), and the causal relations of three levels.
Discovering A Variety of Objects in Spatio-Temporal Human-Object Interactions
In daily HOIs, humans often interact with a variety of objects, e. g., holding and touching dozens of household items in cleaning.
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision.
Constructing Balance from Imbalance for Long-tailed Image Recognition
Previous methods tackle with data imbalance from the viewpoints of data distribution, feature space, and model design, etc.
Mining Cross-Person Cues for Body-Part Interactiveness Learning in HOI Detection
Though significant progress has been made, interactiveness learning remains a challenging problem in HOI detection: existing methods usually generate redundant negative H-O pair proposals and fail to effectively extract interactive pairs.
Ranked #9 on
Human-Object Interaction Detection
on V-COCO
Interactiveness Field in Human-Object Interactions
Human-Object Interaction (HOI) detection plays a core role in activity understanding.
Learning to Anticipate Future with Dynamic Context Removal
Anticipating future events is an essential feature for intelligent systems and embodied AI.
Highlighting Object Category Immunity for the Generalization of Human-Object Interaction Detection
To achieve OC-immunity, we propose an OC-immune network that decouples the inputs from OC, extracts OC-immune representations, and leverages uncertainty quantification to generalize to unseen objects.
HAKE: A Knowledge Engine Foundation for Human Activity Understanding
Human activity understanding is of widespread interest in artificial intelligence and spans diverse applications like health care and behavior analysis.
Human Trajectory Prediction With Momentary Observation
Human trajectory prediction task aims to analyze human future movements given their past status, which is a crucial step for many autonomous systems such as self-driving cars and social robots.
Localization with Sampling-Argmax
In this work, we propose sampling-argmax, a differentiable training method that imposes implicit constraints to the shape of the probability map by minimizing the expectation of the localization error.
Ranked #158 on
3D Human Pose Estimation
on Human3.6M
Learning Single/Multi-Attribute of Object with Symmetry and Group
To model the compositional nature of these concepts, it is a good choice to learn them as transformations, e. g., coupling and decoupling.
Transferable Interactiveness Knowledge for Human-Object Interaction Detection
Human-Object Interaction (HOI) detection is an important problem to understand how humans interact with objects.
Ranked #28 on
Human-Object Interaction Detection
on V-COCO
UKPGAN: A General Self-Supervised Keypoint Detector
Keypoint detection is an essential component for the object registration and alignment.
Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes
In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.
HOI Analysis: Integrating and Decomposing Human-Object Interaction
Meanwhile, isolated human and object can also be integrated into coherent HOI again.
Ranked #20 on
Human-Object Interaction Detection
on V-COCO
DecAug: Augmenting HOI Detection via Decomposition
Human-object interaction (HOI) detection requires a large amount of annotated data.
Ranked #68 on
Domain Generalization
on PACS
Detailed 2D-3D Joint Representation for Human-Object Interaction
In light of these, we propose a detailed 2D-3D joint representation learning method.
Ranked #1 on
Human-Object Interaction Detection
on Ambiguious-HOI
PaStaNet: Toward Human Activity Knowledge Engine
In light of this, we propose a new path: infer human part states first and then reason out the activities based on part-level semantics.
Ranked #3 on
Human-Object Interaction Detection
on HICO
Symmetry and Group in Attribute-Object Compositions
To model the compositional nature of these general concepts, it is a good choice to learn them through transformations, such as coupling and decoupling.
Ranked #1 on
Compositional Zero-Shot Learning
on MIT-States
(Top-1 accuracy % metric)
InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting
With the guidance of such map, we boost the performance of R101-Mask R-CNN on instance segmentation from 35. 7 mAP to 37. 9 mAP without modifying the backbone or network structure.
Ranked #78 on
Instance Segmentation
on COCO test-dev
HAKE: Human Activity Knowledge Engine
To address these and promote the activity understanding, we build a large-scale Human Activity Knowledge Engine (HAKE) based on the human body part states.
Ranked #2 on
Human-Object Interaction Detection
on HICO
(using extra training data)
Transferable Interactiveness Knowledge for Human-Object Interaction Detection
On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results.
Ranked #29 on
Human-Object Interaction Detection
on V-COCO
