GMO-E²DIT is an agentic editing framework that decouples VLM-based planning from mask-conditioned rendering and uses reflection to execute multi-operation e-commerce image edits with error recovery.
Yolov10: Real-time end-to-end object detection.Advances in neural information processing systems, 37:107984–108011, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
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VocaDet detects arbitrary objects by retrieving multi-granularity visual tokens from a sample-built vector database of position-debiased DINOv3 features and topology, without detector training.
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GMO-E$^2$DIT: Grounded Multi-Operation Editing for E-Commerce Images
GMO-E²DIT is an agentic editing framework that decouples VLM-based planning from mask-conditioned rendering and uses reflection to execute multi-operation e-commerce image edits with error recovery.
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VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval
VocaDet detects arbitrary objects by retrieving multi-granularity visual tokens from a sample-built vector database of position-debiased DINOv3 features and topology, without detector training.