Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Diffusion models represent a promising avenue for image generation, having demonstrated
competitive performance in pose-guided person image generation. However, existing …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …

The pose-guided person image generation task requires synthesizing photorealistic images
of humans in arbitrary poses. The existing approaches use generative adversarial networks …

We propose Neural Actor (NA), a new method for high-quality synthesis of humans from
arbitrary viewpoints and under arbitrary controllable poses. Our method is developed upon …

Recent work has showcased the significant potential of diffusion models in pose-guided
person image synthesis. However, owing to the inconsistency in pose between the source …

Image virtual try-on aims to fit a garment image (target clothes) to a person image. Prior
methods are heavily based on human parsing. However, slightly-wrong segmentation …

We study the problem of inferring scene affordances by presenting a method for realistically
inserting people into scenes. Given a scene image with a marked region and an image of a …

Abstract Pose Guided Person Image Generation (PGPIG) is the task of transforming a
person image from the source pose to a given target pose. Most of the existing methods only …