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Our hypothesis is that the appearance of a person -- their pose, clothing, action -- is a powerful cue for localizing the objects they are interacting with.
Ranked #9 on Human-Object Interaction Detection on HICO-DET
Temporal relational reasoning, the ability to link meaningful transformations of objects or entities over time, is a fundamental property of intelligent species.
Ranked #2 on Hand Gesture Recognition on Jester test
We introduce a simple yet surprisingly powerful model to incorporate attention in action recognition and human object interaction tasks.
Ranked #5 on Human-Object Interaction Detection on HICO
Our core idea is that the appearance of a person or an object instance contains informative cues on which relevant parts of an image to attend to for facilitating interaction prediction.
Ranked #4 on Human-Object Interaction Detection on V-COCO
Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance.
Ranked #1 on Human Part Segmentation on CIHP
For a given scene, GPNN infers a parse graph that includes i) the HOI graph structure represented by an adjacency matrix, and ii) the node labels.
Ranked #5 on Human-Object Interaction Detection on V-COCO
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 #3 on Human-Object Interaction Detection on V-COCO
In this work, we exploit the simple observation that actions are accompanied by contextual cues to build a strong action recognition system.
Ranked #4 on Weakly Supervised Object Detection on HICO-DET
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 #1 on Human-Object Interaction Detection on HICO-DET (using extra training data)