Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
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Updated
Jan 15, 2024 - Python
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
🎥 Python and OpenCV-based scene cut/transition detection program & library.
☕ Fast-RCNN and Scene Recognition using Caffe
The World's Leading Cross Platform AI Engine for Edge Devices
Keras code and weights files for the VGG16-places365 and VGG16-hybrid1365 CNNs for scene classification
MR-CNNs for Large-Scale Scene Recognition
PlacenoteSDK Sample app in native iOS using ARKit, written primarily in Swift
this is the code release for ''Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition''
Code repository for paper https://www.sciencedirect.com/science/article/pii/S0031320320300613 @ Pattern Recognition 2020
YAPO e+ - Yet Another Porn Organizer (extended)
EYE-EEG toolbox for combining eye-tracking & EEG
This project is to use deep learning to auto classify the scene images with limited amount of training images.
When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition (CVIU 2022)
Scene recognition by combining local and global image descriptors
[IROS 2020] Indoor Scene Recognition in 3D
Solve classical computer vision topic, image recognition, with simplest method, tiny images and KNN(K Nearest Neighbor) classification, and then move forward to the state-of-the-art techniques, bags of quantized local features and linear classifiers learned by SVC(support vector classifier).
Extended Object Detection is an ROS package and has ample opportunities for describing objects for detection in the video image.
DeepEye is a surveillance application leveraging the current sate of art deep learning and computer vision techniques. Current back-end framework uses Google Object Detection Api for object detection and tracking. It is open-source and feel free to modify for your own usage.
This repository contains the dataset and the source code for the detection of visual relationships with the Logic Tensor Networks framework.
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