Unofficial PyTorch reimplementation of Hand-Biomechanical-Constraints

Hand Biomechanical Constraints Pytorch Unofficial PyTorch reimplementation of Hand-Biomechanical-Constraints (ECCV2020). This project reimplement following components : 3 kinds of biomechanical soft constraints integrate BMC into training procedure (PyTorch version) Usage Download data Download 3D joint location data joints.zip Google Drive or Baidu Pan (2pip), and . These statistics are from following datasets: Note the data from these datasets under their own licenses. Calculate BMC Run the code python calculate_bmc.py You will get bone_len_max.npy bone_len_min.npy for bone length limits curvatures_max.npy curvatures_min.npy […]

Read more

Code for weakly supervised segmentation of a single class

SingleClassRL Implementation of weak single object segmentation from paper “Regularized Loss for Weakly Supervised Single Class Semantic Segmentation”, ECCV2020. PDF Main Files train_with_anneal.py: use for training first in annealing stage, then in normal stage train_with_transfer.py: use from training with weight transfer from another dataset, models that can be used for weight transfer are in directory ‘trained_models’ OxfodPet dataset Download OxfordPet from (https://www.robots.ox.ac.uk/~vgg/data/pets/) Files in ‘SingleClassRLdataOxford_iit_petannotations’ should be placed in the ‘annotation’ directory of OxfordPet dataset GitHub https://github.com/morduspordus/SingleClassRL    

Read more

Cross Attention in Vision Transformer with python

CAT: Cross Attention in Vision Transformer This is official implement of “CAT: Cross Attention in Vision Transformer”. Abstract Since Transformer has found widespread use in NLP, the potential of Transformer in CV has been realized and has inspired many new approaches. However, the computation required for replacing word tokens with image patches for Transformer after the tokenization of the image is vast(e.g., ViT), which bottlenecks model training and inference. In this paper, we propose a new attention mechanism in Transformer […]

Read more

Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals

LapDepth-release This repository is a Pytorch implementation of the paper “Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals” Minsoo Song, Seokjae Lim, and Wonjun Kim*IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) Requirements Python >= 3.7 Pytorch >= 1.6.0 Ubuntu 16.04 CUDA 9.2 cuDNN (if CUDA available) some other packages: geffnet, path, IPython, blessings, progressbar Pretrained models You can download pre-trained model Demo images (Single Test Image Prediction) Make sure you download the pre-trained model and placed it […]

Read more

Why must text data be pre-processed ?

This article was published as a part of the Data Science Blogathon Introduction Language is a structured medium we humans use to communicate with each other. Language can be in the form of speech or text. “Blah blah”, “Meh”, “zzzz…” Yup, we can understand these words. But the question is, “Can computers understand these?” Nop, machines can’t understandthese. In fact, machines can’t understand any text data at all, be it the word “blah” or the word “machine”. They only understand numbers. […]

Read more
1 49 50 51