Showing 1-18 of 18 projects
Object detection toolbox for PyTorch with support for multiple tasks and state-of-the-art models.
End-to-end object detection library using Transformers, a powerful computer vision technique.
PaddleDetection is an open-source object detection toolkit based on the PaddlePaddle deep learning framework, supporting various computer vision tasks.
A collection of tutorials and notebooks on state-of-the-art computer vision models and techniques for developers.
TensorRT implementation of popular deep learning networks for efficient inference on GPUs
RF-DETR is a SOTA real-time object detection and segmentation model architecture designed for fine-tuning.
Real-time object detection transformer that outperforms YOLOs, built with Paddle PyTorch.
Deformable DETR is a state-of-the-art object detection model that uses deformable transformers for end-to-end detection.
A curated collection of papers and resources about transformer models for computer vision applications.
A powerful object detection and instance segmentation library built on top of YOLOv7 and transformers, with TensorRT acceleration.
A library that redefines the regression task of DETRs as a fine-grained distribution refinement problem, with potential applications in object detection.
A Python library focused on improving YOLO models for object detection and computer vision tasks.
Official implementation of the DETR object detection paper with improved DeNoising Anchor Boxes
DEIM: A real-time object detection system using DETR with improved matching for fast convergence.
A curated list of recent Transformer-based computer vision papers and implementations.
A C++ library for accelerating YOLO-based computer vision models using NVIDIA's TensorRT framework.
All-in-one training for vision models with pretraining, fine-tuning, and distillation capabilities.
Collaborative hybrid assignments training for DETRs, a novel object detection model.
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