Search Results for author:
Found 5 papers, 4 papers with code
Learning Structured Representations of Visual Scenes
As the intermediate-level representations bridging the two levels, structured representations of visual scenes, such as visual relationships between pairwise objects, have been shown to not only benefit compositional models in learning to reason along with the structures but provide higher interpretability for model decisions.
Human-Object Interaction Detection
Representation Learning
+2
Recovering the Unbiased Scene Graphs from the Biased Ones
Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects.
Ranked #3 on
Unbiased Scene Graph Generation
on Visual Genome
ST-HOI: A Spatial-Temporal Baseline for Human-Object Interaction Detection in Videos
Detecting human-object interactions (HOI) is an important step toward a comprehensive visual understanding of machines.
Ranked #3 on
Human-Object Interaction Anticipation
on VidHOI
Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations
Visual relationship detection aims to reason over relationships among salient objects in images, which has drawn increasing attention over the past few years.
Zero-Shot Multi-View Indoor Localization via Graph Location Networks
In this paper, we propose a novel neural network based architecture Graph Location Networks (GLN) to perform infrastructure-free, multi-view image based indoor localization.
