1583 Open source projects that are alternatives of or similar to Deep Learning For Tracking And Detection

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The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

Papers and Datasets about Point Cloud.

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🎨 🎨 深度学习 卷积神经网络教程 ：图像识别，目标检测，语义分割，实例分割，人脸识别，神经风格转换，GAN等🎨🎨 https://dataxujing.github.io/CNN-paper2/

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Single Shot Tracker

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Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

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Free to use online tool for labelling photos. https://makesense.ai

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[ECCV'20] Ocean: Object-aware Anchor-Free Tracking

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Real-time object detection on Android using the YOLO network with TensorFlow

Video++, a C++14 high performance video and image processing library.

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ImageNet 2015 Object Detection from Video (VID)

ICCV2019最新录用情况

PyTorch extensions for fast R&D prototyping and Kaggle farming

Convert any classification model or architecture trained in keras to an object detection model

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YOLOv3 implementation in TensorFlow 2.3.1

BRFv4 - HTML5/Javascript - examples project. Reference implementation for all other platform example packages.

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

💎 Detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).

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Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

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An image recognition/object detection model that detects handwritten digits and simple math operators. The output of the predicted objects (numbers & math operators) is then evaluated and solved.

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