5 papers
Visual Commonsense Driven Knowledge Refinements for Scene Graph Generation
Maëlic Neau, Salim Baloch, Jakob Suchan +2
Learning-driven Scene Graph Generation (SGG) models excel on frequent relation types but degrade sharply under annotation sparsity, failing to capture reliable visual commonsense k…
REACT++: Efficient Cross-Attention for Real-Time Scene Graph Generation
Maëlic Neau, Zoe Falomir
Scene Graph Generation (SGG) is a task that encodes visual relationships between objects in images as graph structures. SGG shows significant promise as a foundational component fo…
GraSP-VLA: Graph-based Symbolic Action Representation for Long-Horizon Planning with VLA Policies
Maëlic Neau, Zoe Falomir, Paulo E. Santos +2
Deploying autonomous robots that can learn new skills from demonstrations is an important challenge of modern robotics. Existing solutions often apply end-to-end imitation learning…
REACT: Real-time Efficiency and Accuracy Compromise for Tradeoffs in Scene Graph Generation
Maëlic Neau, Paulo E. Santos, Anne-Gwenn Bosser +2
Scene Graph Generation (SGG) is a task that encodes visual relationships between objects in images as graph structures. SGG shows significant promise as a foundational component fo…
Measuring Image-Relation Alignment: Reference-Free Evaluation of VLMs and Synthetic Pre-training for Open-Vocabulary Scene Graph Generation
Maëlic Neau, Zoe Falomir, Cédric Buche +1
Scene Graph Generation (SGG) encodes visual relationships between objects in images as graph structures. Thanks to the advances of Vision-Language Models (VLMs), the task of Open-V…