RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
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Updated
Aug 5, 2026 - Python
RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
Production-ready C++/TensorRT inference engine for RF-DETR. Object detection and instance segmentation with FP32/FP16/INT8 support. Optimized for NVIDIA GPUs, Jetson (Orin, AGX Thor).
C++ app for computer vision inference, supporting multiple tasks and backends.
ONNX model with inference, conversion and visualization scripts for RF-DETR (object detection and instance segmentation)
NVIDIA DeepStream SDK 8.0 / 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 application for YOLO-Segmentation models
Object tracking pipelines complete with RF-DETR, YOLOv9, YOLO-NAS, YOLOv8, and YOLOv7 detection and BYTETracker tracking
RF-DETR C++ tensorrt : Real-Time End-to-End Object Detection
Run RF-DETR on NVIDIA DeepStream
C++ application to perform computer vision tasks using Nvidia Triton Server for model inference
Low-latency RF-DETR video stream inference in Rust using zero-copy mmap + FlatBuffers
RF-DETR C++ inference engine for object detection and instance segmentation with ONNX Runtime and TensorRT support
RF-DETR Object Detection with DeepSORT Tracking
RF-DETR + USLS: object detection using Rust
Real-time neural-vision libraries for NVIDIA Jetson Orin — Rust + TensorRT inference with GPU pre/post-processing.
Visualize what RF-DETR's backbone sees during inference.
YOLOv26 and RF-DETR object detection for civilians, rescuers, and animals in disaster scenarios. Real-time support for emergency response in floods and structural collapses.
One‑line fine‑tuning of RF‑DETR on selected classes from OpenImages V7
Advanced real-time football tracking system using RF-DETR, Extended Kalman Filter, and an intelligent virtual camera. Production-grade pipeline for sports broadcasting with low-latency RTMP/YouTube streaming, PID-controlled smoothing, and trajectory prediction.
Standardized evaluation of modern object detectors beyond COCO.
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