Hepsiburada - Hepsiburada Urun Bilgisi Cekme

Last update: Oct 26, 2022

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Overview

Hepsiburada Urun Bilgisi Cekme

from hepsiburada import Marka
nike = Marka("nike")
nike.sayfalar()

nike.urunler(sayfano=3)

for sku, urun in nike.urun_listesi.items():
    print(sku, urun.price)

Owner

Ilker Manap

GitHub Repository

Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.

Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B

162 Dec 16, 2022

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

213 Dec 27, 2022

A new benchmark for Icon Question Answering (IconQA) and a large-scale icon dataset Icon645.

IconQA About IconQA is a new diverse abstract visual question answering dataset that highlights the importance of abstract diagram understanding and c

24 Dec 30, 2022

Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).

Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma This repo provi

99 Dec 27, 2022

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Advances in Financial Machine Learning Exercises Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by

1.4k Jan 04, 2023

Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.

Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm

12 Nov 09, 2022

Hepsiburada - Hepsiburada Urun Bilgisi Cekme

Related tags

Overview

Hepsiburada Urun Bilgisi Cekme

Owner

Ilker Manap

Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

A new benchmark for Icon Question Answering (IconQA) and a large-scale icon dataset Icon645.

Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.

RIM: Reliable Influence-based Active Learning on Graphs.

A decent AI that solves daily Wordle puzzles. Works with different websites with similar wordlists,.

Implementation of Memory-Compressed Attention, from the paper "Generating Wikipedia By Summarizing Long Sequences"

「PyTorch Implementation of AnimeGANv2」を用いて、生成した顔画像を元の画像に上書きするデモ

[ACM MM 2019 Oral] Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking

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

RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

Official Pytorch implementation for "End2End Occluded Face Recognition by Masking Corrupted Features, TPAMI 2021"

Semi-supervised Implicit Scene Completion from Sparse LiDAR

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

[SIGGRAPH Asia 2021] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning.

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

The object detection pipeline is based on Ultralytics YOLOv5