Total Selfie: Generating Full-Body Selfies

• URL: http://arxiv.org/abs/2308.14740v2
• Date: Wed, 3 Apr 2024 17:42:44 GMT
• Title: Total Selfie: Generating Full-Body Selfies
• Authors: Bowei Chen, Brian Curless, Ira Kemelmacher-Shlizerman, Steven M. Seitz,
• Abstract summary: We present a method to generate full-body selfies from photographs originally taken at arms length. Our approach takes as input four selfies of your face and body, a background image, and generates a full-body selfie in a desired target pose.
• Score: 21.020454186769655
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a method to generate full-body selfies from photographs originally taken at arms length. Because self-captured photos are typically taken close up, they have limited field of view and exaggerated perspective that distorts facial shapes. We instead seek to generate the photo some one else would take of you from a few feet away. Our approach takes as input four selfies of your face and body, a background image, and generates a full-body selfie in a desired target pose. We introduce a novel diffusion-based approach to combine all of this information into high-quality, well-composed photos of you with the desired pose and background.

Related papers

• Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps [30.970209890835793]
  We explore how to create a professional'' version of a person's photograph.<n>A key challenge is to preserve the person's unique identity, face and body features while transforming the photo.<n>Our approach yields high-quality, reposed portraits and achieves strong qualitative and quantitative performance on real-world imagery.
  arXiv  Detail & Related papers  (2025-12-19T00:40:53Z)
• Teleportraits: Training-Free People Insertion into Any Scene [59.76038137014233]
  We introduce a unified training-free pipeline that leverages pre-trained text-to-image diffusion models.<n>We show that diffusion models inherently possess the knowledge to place people in complex scenes without requiring task-specific training.<n>Our method achieves affordance-aware global editing, seamlessly inserting people into scenes.
  arXiv  Detail & Related papers  (2025-10-07T08:12:57Z)
• Generative Modeling of Shape-Dependent Self-Contact Human Poses [48.30189394803952]
  Despite its relevance, existing self-contact datasets lack variety of self-contact poses and precise body shapes.<n>We introduce the first extensive self-contact dataset with precise body shape registration, Goliath-SC, consisting of 383K self-contact poses across 130 subjects.<n>We propose generative modeling of self-contact prior conditioned by body shape parameters, based on a body-part-wise latent diffusion with self-attention.
  arXiv  Detail & Related papers  (2025-09-27T16:26:38Z)
• DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior [82.9526308672547]
  We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses.<n>Our approach unifies various pose-centric tasks as inverse problems, solving them through variational diffusion sampling.<n>Our model consistently outperforms state-of-the-art alternatives, establishing a new benchmark for whole-body human pose prior modeling.
  arXiv  Detail & Related papers  (2025-08-01T12:56:39Z)
• AvatarMakeup: Realistic Makeup Transfer for 3D Animatable Head Avatars [89.31582684550723]
  AvatarMakeup achieves state-of-the-art makeup transfer quality and consistency throughout animation.<n>Coherent Duplication optimize a global UV map by recoding the averaged facial attributes among the generated makeup images.<n>Experiments demonstrate that AvatarMakeup achieves state-of-the-art makeup transfer quality and consistency throughout animation.
  arXiv  Detail & Related papers  (2025-07-03T08:26:57Z)
• ID-Cloak: Crafting Identity-Specific Cloaks Against Personalized Text-to-Image Generation [54.14901999875917]
  We investigate the creation of identity-specific cloaks that safeguard all images belong to a specific identity. We craft identity-specific cloaks with the proposed novel objective that encourages the cloak to guide the model away from its normal output. Our method, along with the proposed identity-specific cloak setting, marks a notable advance in realistic privacy protection.
  arXiv  Detail & Related papers  (2025-02-12T03:52:36Z)
• Context-Aware Full Body Anonymization using Text-to-Image Diffusion Models [1.5088726951324294]
  Anonymization plays a key role in protecting sensible information of individuals in real world datasets. In this paper, we propose a workflow for full body person anonymization utilizing Stable Diffusion as a generative backend. We show that our method outperforms state-of-the art anonymization pipelines with respect to image quality, resolution, Inception Score (IS) and Frechet Inception Distance (FID)
  arXiv  Detail & Related papers  (2024-10-11T06:04:30Z)
• SUPER: Selfie Undistortion and Head Pose Editing with Identity Preservation [37.89326064230339]
  Super is a novel method of eliminating distortions and adjusting head pose in a close-up face crop. We perform 3D GAN inversion for a facial image by optimizing camera parameters and face latent code. We estimate depth from the obtained latent code, create a depth-induced 3D mesh, and render it with updated camera parameters to obtain a warped portrait.
  arXiv  Detail & Related papers  (2024-06-18T15:14:14Z)
• Selfie Taking with Facial Expression Recognition Using Omni-directional Camera [0.0]
  We propose a method to take selfies with multiple people using an omni-directional camera. Specifically, a user takes a few seconds of video with an omni-directional camera, followed by face detection on all frames. After performing facial expression recognition on all the frames, the proposed method finally extracts the frame in which the participants are happiest.
  arXiv  Detail & Related papers  (2024-05-25T01:07:29Z)
• URHand: Universal Relightable Hands [64.25893653236912]
  We present URHand, the first universal relightable hand model that generalizes across viewpoints, poses, illuminations, and identities. Our model allows few-shot personalization using images captured with a mobile phone, and is ready to be photorealistically rendered under novel illuminations.
  arXiv  Detail & Related papers  (2024-01-10T18:59:51Z)
• VINECS: Video-based Neural Character Skinning [82.39776643541383]
  We propose a fully automated approach for creating a fully rigged character with pose-dependent skinning weights. We show that our approach outperforms state-of-the-art while not relying on dense 4D scans.
  arXiv  Detail & Related papers  (2023-07-03T08:35:53Z)
• Photoswap: Personalized Subject Swapping in Images [56.2650908740358]
  Photoswap learns the visual concept of the subject from reference images and swaps it into the target image using pre-trained diffusion models. Photoswap significantly outperforms baseline methods in human ratings across subject swapping, background preservation, and overall quality.
  arXiv  Detail & Related papers  (2023-05-29T17:56:13Z)
• UPGPT: Universal Diffusion Model for Person Image Generation, Editing and Pose Transfer [15.15576618501609]
  Text-to-image models (T2I) have been used to generate high quality images of people. However, due to the random nature of the generation process, the person has a different appearance. We propose a multimodal diffusion model that accepts text, pose, and visual prompting.
  arXiv  Detail & Related papers  (2023-04-18T10:05:37Z)
• HumanGAN: A Generative Model of Humans Images [78.6284090004218]
  We present a generative model for images of dressed humans offering control over pose, local body part appearance and garment style. Our model encodes part-based latent appearance vectors in a normalized pose-independent space and warps them to different poses, it preserves body and clothing appearance under varying posture.
  arXiv  Detail & Related papers  (2021-03-11T19:00:38Z)
• PoNA: Pose-guided Non-local Attention for Human Pose Transfer [105.14398322129024]
  We propose a new human pose transfer method using a generative adversarial network (GAN) with simplified cascaded blocks. Our model generates sharper and more realistic images with rich details, while having fewer parameters and faster speed.
  arXiv  Detail & Related papers  (2020-12-13T12:38:29Z)
• Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild [57.944605468653414]
  In selfies, constraints such as human arm length often make the body pose look unnatural. We introduce $textitunselfie$, a novel photographic transformation that automatically translates a selfie into a neutral-pose portrait. We propose a novel nearest pose search module that makes the reposing task easier and enables the generation of multiple neutral-pose results.
  arXiv  Detail & Related papers  (2020-07-29T19:21:02Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.