arXiv Computer Vision
RT-DETR-World: Transferring Rich LLM Semantics to Real-Time Open-Vocabulary Detection
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
Hugging Face Trending Papers
6d ago
RT-DETR-World: Transferring Rich LLM Semantics to Real-Time Open-Vocabulary Detection
Open-vocabulary detection (OVD) recognizes categories unseen during training through textual category queries, yet achieving strong generalization with real-time efficiency remains challenging. Beyond...
arXiv Computer Vision
Sep 14
RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs
arXiv:2609.12552v1 Announce Type: new Abstract: Open-vocabulary detection accepts any class list at inference, and promptable segmentation returns regions without class names: the taxonomy has left t...
arXiv Computer Vision
Aug 25
OvDSGG: End-to-End Open-Vocabulary Dynamic Scene Graph Generation
arXiv:2608.14835v2 Announce Type: replace Abstract: Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as $\langle$subject, predicate, object$\rangle$ triplets, and underp...
Hugging Face Trending Papers
Jul 27
Multimodal Semantic-Probabilistic Objectness for Open World Object Detection
Open-world object detection (OWOD) requires a detector to recognize known categories, discover unnamed objects from unseen categories, and incrementally learn newly annotated classes. PROB improves unknown discovery by modeling class-agnostic probabilistic objectness in the decoder-query space.
arXiv AI
Jul 28
Multimodal Semantic-Probabilistic Objectness for Open World Object Detection
arXiv:2607. 23981v1 Announce Type: cross Abstract: Open-world object detection (OWOD) requires a detector to recognize known categories, discover unnamed objects from unseen categories, and incrementally learn newly annotated classes.
arXiv AI
Jul 10
VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval
arXiv:2607. 08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories.