3 papers
cs.CV2026
DetPO: In-Context Learning with Multi-Modal LLMs for Few-Shot Object Detection
Gautam Rajendrakumar Gare, Neehar Peri, Matvei Popov +3
Multi-Modal LLMs (MLLMs) demonstrate strong visual grounding capabilities on popular object detection benchmarks like OdinW-13 and RefCOCO. However, state-of-the-art models still s…
cs.CV2026★ 3 cited
RF-DETR: Neural Architecture Search for Real-Time Detection Transformers
Isaac Robinson, Peter Robicheaux, Matvei Popov +2
Open-vocabulary detectors achieve impressive performance on COCO, but often fail to generalize to real-world datasets with out-of-distribution classes not typically found in their…
cs.CV2025
Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models
Peter Robicheaux, Matvei Popov, Anish Madan +4
Vision-language models (VLMs) trained on internet-scale data achieve remarkable zero-shot detection performance on common objects like car, truck, and pedestrian. However, state-of…