10 papers with code • 0 benchmarks • 0 datasets

Given an image, generate variations of the image

Most implemented papers

Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

omarsayed7/Deep-Emotion 4 Feb 2019

In recent years, several works proposed an end-to-end framework for facial expression recognition, using deep learning models.

Versatile Diffusion: Text, Images and Variations All in One Diffusion Model

shi-labs/versatile-diffusion ICCV 2023

In this work, we expand the existing single-flow diffusion pipeline into a multi-task multimodal network, dubbed Versatile Diffusion (VD), that handles multiple flows of text-to-image, image-to-text, and variations in one unified model.

Real-World Image Variation by Aligning Diffusion Inversion Chain

dvlab-research/rival NeurIPS 2023

Our pipeline enhances the generation quality of image variations by aligning the image generation process to the source image's inversion chain.

A Geometric Analysis of Deep Generative Image Models and Its Applications

Animadversio/GAN-Geometry ICLR 2021

We show that the use of this metric allows for more efficient optimization in the latent space (e. g. GAN inversion) and facilitates unsupervised discovery of interpretable axes.

The Geometry of Deep Generative Image Models and its Applications

Animadversio/GAN-Geometry 15 Jan 2021

Our results illustrate that defining the geometry of the GAN image manifold can serve as a general framework for understanding GANs.

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video

toyotaresearchinstitute/remoteppg ICCV 2021

The ability to reliably estimate physiological signals from video is a powerful tool in low-cost, pre-clinical health monitoring.

AugStatic - A Light-Weight Image Augmentation Library

avs-abhishek123/AugStatic Journal of Emerging Technologies and Innovative Research (JETIR) 2022

AugStatic is a custom-built image augmentation library with lower computation costs and more extraordinary salient features compared to other image augmentation libraries.

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

shi-labs/prompt-free-diffusion 25 May 2023

Text-to-image (T2I) research has grown explosively in the past year, owing to the large-scale pre-trained diffusion models and many emerging personalization and editing approaches.