HyperAIHyperAI

Command Palette

Search for a command to run...

المنصة

Open Vocabulary Object Detection On Mscoco

المقاييس

AP 0.5

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

Paper Title
Cooperative Foundational Models50.3Enhancing Novel Object Detection via Cooperative Foundational Models
DE-ViT50Detect Everything with Few Examples
DITO46.1Region-centric Image-Language Pretraining for Open-Vocabulary Detection
OV-DQUO(RN50x4)45.6OV-DQUO: Open-Vocabulary DETR with Denoising Text Query Training and Open-World Unknown Objects Supervision
LP-OVOD (OWL-ViT Proposals)44.9LP-OVOD: Open-Vocabulary Object Detection by Linear Probing
CLIPSelf44.3CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
CORA+43.1CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching
BARON42.7Aligning Bag of Regions for Open-Vocabulary Object Detection
SIA-OVD (RN50x4)41.9SIA-OVD: Shape-Invariant Adapter for Bridging the Image-Region Gap in Open-Vocabulary Detection
CORA41.7CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching
RALF41.3Retrieval-Augmented Open-Vocabulary Object Detection
LP-OVOD40.5LP-OVOD: Open-Vocabulary Object Detection by Linear Probing
Region-CLIP (RN50x4-C4)39.3RegionCLIP: Region-based Language-Image Pretraining
OV-DQUO(R50)39.2OV-DQUO: Open-Vocabulary DETR with Denoising Text Query Training and Open-World Unknown Objects Supervision
Object-Centric-OVD36.9Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection
CLIM (RN50)36.9CLIM: Contrastive Language-Image Mosaic for Region Representation
OADP (G-OVD)35.6Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection
SIA-OVD (RN50)35.5SIA-OVD: Shape-Invariant Adapter for Bridging the Image-Region Gap in Open-Vocabulary Detection
VL-PLM (RN50)34.4Exploiting Unlabeled Data with Vision and Language Models for Object Detection
CFM-ViT34.1Contrastive Feature Masking Open-Vocabulary Vision Transformer
0 of 30 row(s) selected.