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Found 7 papers, 5 papers with code
Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning
Human object interaction (HOI) detection plays a crucial role in human-centric scene understanding and serves as a fundamental building-block for many vision tasks.
Human-Object Interaction Detection
Knowledge Distillation
+2
Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling
We introduce a new task, unsupervised vision-language (VL) grammar induction.
Single Image 3D Object Estimation with Primitive Graph Networks
To address those challenges, we adopt a primitive-based representation for 3D object, and propose a two-stage graph network for primitive-based 3D object estimation, which consists of a sequential proposal module and a graph reasoning module.
Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation
Scene graph generation is an important visual understanding task with a broad range of vision applications.
Relation-aware Instance Refinement for Weakly Supervised Visual Grounding
Visual grounding, which aims to build a correspondence between visual objects and their language entities, plays a key role in cross-modal scene understanding.
Learning Cross-modal Context Graph for Visual Grounding
To address their limitations, this paper proposes a language-guided graph representation to capture the global context of grounding entities and their relations, and develop a cross-modal graph matching strategy for the multiple-phrase visual grounding task.
Pose-aware Multi-level Feature Network for Human Object Interaction Detection
Reasoning human object interactions is a core problem in human-centric scene understanding and detecting such relations poses a unique challenge to vision systems due to large variations in human-object configurations, multiple co-occurring relation instances and subtle visual difference between relation categories.
