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attentions icon attentions

Programming Assignment 1 for KAIST EE898 2019 Spring

channel-pruning icon channel-pruning

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

cnn_randrnn icon cnn_randrnn

When CNNs Meet Random RNNs: Towards Multi-Level Analysis for RGB-D Object and Scene Recognition

crnn icon crnn

Convolutional-Recursive Deep Learning for 3D Object Classification Richard Socher, Brody Huval, Bharath Bhat, Christopher D. Manning and Andrew Y. Ng Advances in Neural Information Processing Systems (NIPS 2012)

cs231a_project icon cs231a_project

This problem takes an input of an RGB-D image in the NYU-RGBD dataset. The goal is to perform 3D object recognition and indoor scene classification. These two tasks are tackled jointly in our holistic model, that is, some constraints are placed among scenes and these objects when reasoning about object detection, which helps boost the performance of scene classification and object detection.

deep-prior icon deep-prior

Fast and accurate 3D hand pose estimation from single depth images

imgaug icon imgaug

Image augmentation for machine learning experiments.

models icon models

Models and examples built with TensorFlow

multimodaldl icon multimodaldl

This model implementation of 'Multimodal Deep Learning for Robust RGB-D Object Recognition'

nideep icon nideep

collection of utilities to use with deep learning libraries (e.g. caffe)

rcfusion icon rcfusion

Original implementation of the paper "Recurrent Convolutional Fusion for RGB-D Object Recognition": https://arxiv.org/pdf/1806.01673.pdf

rcnn-depth icon rcnn-depth

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

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