85 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Video-to-Video Synthesis

NVIDIA/vid2vid NeurIPS 2018

We study the problem of video-to-video synthesis, whose goal is to learn a mapping function from an input source video (e. g., a sequence of semantic segmentation masks) to an output photorealistic video that precisely depicts the content of the source video.

Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting

Atlas200dk/sample-imageinpainting-HiFill CVPR 2020

Since convolutional layers of the neural network only need to operate on low-resolution inputs and outputs, the cost of memory and computing power is thus well suppressed.

Hyena Hierarchy: Towards Larger Convolutional Language Models

hazyresearch/safari 21 Feb 2023

Recent advances in deep learning have relied heavily on the use of large Transformers due to their ability to learn at scale.

Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN

vinthony/ghost-free-shadow-removal 20 Nov 2019

With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images.

ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

Xiangtaokong/ClassSR CVPR 2021

On this basis, we propose a new solution pipeline -- ClassSR that combines classification and SR in a unified framework.

Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce

flipkart-incubator/fk-visual-search 7 Mar 2017

In this paper, we present a unified end-to-end approach to build a large scale Visual Search and Recommendation system for e-commerce.

A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models

QData/JEEK ICML 2018

We consider the problem of including additional knowledge in estimating sparse Gaussian graphical models (sGGMs) from aggregated samples, arising often in bioinformatics and neuroimaging applications.

Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking

chanzuckerberg/MedMentions ACL 2018

Extraction from raw text to a knowledge base of entities and fine-grained types is often cast as prediction into a flat set of entity and type labels, neglecting the rich hierarchies over types and entities contained in curated ontologies.

Vision-and-Dialog Navigation

mmurray/cvdn 10 Jul 2019

To train agents that search an environment for a goal location, we define the Navigation from Dialog History task.