This repo contains the implementation of our paper: DeepDPM: Deep Clustering With An Unknown Number of Clusters Meitar Ronen, Shahaf Finder and Oren Freifeld. DeepDPM clustering example on 2D data. On the left: DeepDPM’s predicted clusters’ assignments, centers and covariances. On the right: Clusters colored by the GT labels, and the net’s decision boundary. Examples of the clusters found by DeepDPM on the ImageNet Dataset: Table of Contents Introduction Installation Training Citation    

Introduction This repo contains PyTorch implementation for paper Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement (CVPR2022) @inproceedings{xu2022br, author = {Xu, Xiuwei and Wang, Yifan and Zheng, Yu and Rao, Yongming and Lu, Jiwen and Zhou, Jie}, title = {Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2022}    

StrongSORT: Make DeepSORT Great Again StrongSORT: Make DeepSORT Great Again Yunhao Du, Yang Song, Bo Yang, Yanyun Zhao arxiv 2202.13514 Abstract Existing Multi-Object Tracking (MOT) methods can be roughly classified as tracking-by-detection and joint-detection-association paradigms. Although the latter has elicited more attention and demonstrates comparable performance relative to the former, we claim that the tracking-by-detection paradigm is still the optimal solution in terms of tracking accuracy. In this paper, we revisit the classic tracker DeepSORT and upgrade it from various […]

This repository show the code to remove the background of the pictures using the U2Net pre-trained model. @InProceedings{Qin_2020_PR, title = {U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection}, author = {Qin, Xuebin and Zhang, Zichen and Huang, Chenyang and Dehghan, Masood and Zaiane, Osmar and Jagersand, Martin}, journal = {Pattern Recognition}, volume = {106}, pages = {107404}, year = {2020}    

(NEW!) Boost Your Own depth with our new repo We present a stand-alone implementation of our Merging Operator. This new repo allows using any pair of monocular depth estimations in our double estimation. This includes using separate networks for base and high-res estimations, using networks not supported by this repo (such as Midas-v3), or using manually edited depth maps for artistic use. This will also be useful for scientists developing CNN-based MDE as a way to quickly apply double estimation […]

This python library predicts the punctuation of English, Italian, French and German texts. We developed it to restore the punctuation of transcribed spoken language. This uses our “FullStop” model that we trained on the Europarl Dataset. Please note that this dataset consists of political speeches. Therefore the model might perform differently on texts from other domains. The code restores the following punctuation markers: “.” “,” “?” “-” “:” Install To get started install the package from pypi: pip install deepmultilingualpunctuation […]