activity
20162026
most citedVNect: Real-time 3D Human Pose Estimation with a Single RGB Camera

1.2k citations · 1.7k across the 48 of their papers we have counts for

collaborators

54 papers

cs.CV2026

STEER: Steerable Dyadic Head Avatars

Kartik Teotia, Helge Rhodin, Hyeongwoo Kim +2

Facial movement and expression are central to face-to-face communication, conveying turn-taking, attention, agreement, and engagement alongside speech. While speech-driven facial a…

cs.CV2026

E-3DPSM: A State Machine for Event-Based Egocentric 3D Human Pose Estimation

Mayur Deshmukh, Hiroyasu Akada, Helge Rhodin +2

Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolution, high dynamic range, and…

cs.CV2025

Audio-Driven Universal Gaussian Head Avatars

Kartik Teotia, Helge Rhodin, Mohit Mendiratta +3

We introduce the first method for audio-driven universal photorealistic avatar synthesis, combining a person-agnostic speech model with our novel Universal Head Avatar Prior (UHAP)…

cs.CV2025

Follow My Hold: Hand-Object Interaction Reconstruction through Geometric Guidance

Ayce Idil Aytekin, Helge Rhodin, Rishabh Dabral +1

We propose a novel diffusion-based framework for reconstructing 3D geometry of hand-held objects from monocular RGB images by leveraging hand-object interaction as geometric guidan…

cs.CV2025

DreamTexture: Shape from Virtual Texture with Analysis by Augmentation

Ananta R. Bhattarai, Xingzhe He, Alla Sheffer +1

DreamFusion established a new paradigm for unsupervised 3D reconstruction from virtual views by combining advances in generative models and differentiable rendering. However, the u…

cs.CV2024

Gaussian Shadow Casting for Neural Characters

Luis Bolanos, Shih-Yang Su, Helge Rhodin

Neural character models can now reconstruct detailed geometry and texture from video, but they lack explicit shadows and shading, leading to artifacts when generating novel views a…

cs.CV2023★ 2 cited

A Data Perspective on Enhanced Identity Preservation for Diffusion Personalization

Xingzhe He, Zhiwen Cao, Nicholas Kolkin +4

Large text-to-image models have revolutionized the ability to generate imagery using natural language. However, particularly unique or personal visual concepts, such as pets and fu…

cs.CV2023

Pose Modulated Avatars from Video

Chunjin Song, Bastian Wandt, Helge Rhodin

It is now possible to reconstruct dynamic human motion and shape from a sparse set of cameras using Neural Radiance Fields (NeRF) driven by an underlying skeleton. However, a chall…

cs.CV2023

Mirror-Aware Neural Humans

Daniel Ajisafe, James Tang, Shih-Yang Su +2

Human motion capture either requires multi-camera systems or is unreliable when using single-view input due to depth ambiguities. Meanwhile, mirrors are readily available in urban…

cs.CV2023★ 1 cited

NPC: Neural Point Characters from Video

Shih-Yang Su, Timur Bagautdinov, Helge Rhodin

High-fidelity human 3D models can now be learned directly from videos, typically by combining a template-based surface model with neural representations. However, obtaining a templ…

cs.CV2023

Few-shot Geometry-Aware Keypoint Localization

Xingzhe He, Gaurav Bharaj, David Ferman +2

Supervised keypoint localization methods rely on large manually labeled image datasets, where objects can deform, articulate, or occlude. However, creating such large keypoint labe…

cs.CV2022

Scaling Neural Face Synthesis to High FPS and Low Latency by Neural Caching

Frank Yu, Sid Fels, Helge Rhodin

Recent neural rendering approaches greatly improve image quality, reaching near photorealism. However, the underlying neural networks have high runtime, precluding telepresence and…

cs.CV2022★ 1 cited

UNeRF: Time and Memory Conscious U-Shaped Network for Training Neural Radiance Fields

Abiramy Kuganesan, Shih-yang Su, James J. Little +1

Neural Radiance Fields (NeRFs) increase reconstruction detail for novel view synthesis and scene reconstruction, with applications ranging from large static scenes to dynamic human…

cs.CV2022★ 1 cited

LatentKeypointGAN: Controlling Images via Latent Keypoints -- Extended Abstract

Xingzhe He, Bastian Wandt, Helge Rhodin

Generative adversarial networks (GANs) can now generate photo-realistic images. However, how to best control the image content remains an open challenge. We introduce LatentKeypoin…

cs.CV2022★ 11 cited

AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints

Xingzhe He, Bastian Wandt, Helge Rhodin

Structured representations such as keypoints are widely used in pose transfer, conditional image generation, animation, and 3D reconstruction. However, their supervised learning re…

cs.CV2022★ 1 cited

DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks

Shih-Yang Su, Timur Bagautdinov, Helge Rhodin

Deep learning greatly improved the realism of animatable human models by learning geometry and appearance from collections of 3D scans, template meshes, and multi-view imagery. Hig…

cs.CV2022

A Simple Method to Boost Human Pose Estimation Accuracy by Correcting the Joint Regressor for the Human3.6m Dataset

Eric Hedlin, Helge Rhodin, Kwang Moo Yi

Many human pose estimation methods estimate Skinned Multi-Person Linear (SMPL) models and regress the human joints from these SMPL estimates. In this work, we show that the most wi…

cs.CV2022

Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment

Paritosh Parmar, Amol Gharat, Helge Rhodin

Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout form naturally requires estimating human…

cs.CV2021★ 4 cited

Improved 2D Keypoint Detection in Out-of-Balance and Fall Situations -- combining input rotations and a kinematic model

Michael Zwölfer, Dieter Heinrich, Kurt Schindelwig +4

Injury analysis may be one of the most beneficial applications of deep learning based human pose estimation. To facilitate further research on this topic, we provide an injury spec…

cs.CV2021★ 2 cited

ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses

Bastian Wandt, James J. Little, Helge Rhodin

Human pose estimation from single images is a challenging problem that is typically solved by supervised learning. Unfortunately, labeled training data does not yet exist for many…

cs.CV2021★ 1 cited

AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation

Mohsen Gholami, Bastian Wandt, Helge Rhodin +2

This paper addresses the problem of cross-dataset generalization of 3D human pose estimation models. Testing a pre-trained 3D pose estimator on a new dataset results in a major per…

cs.CV2021★ 1 cited

GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation

Xingzhe He, Bastian Wandt, Helge Rhodin

Segmenting an image into its parts is a frequent preprocess for high-level vision tasks such as image editing. However, annotating masks for supervised training is expensive. Weakl…

cs.CV2021

NRST: Non-rigid Surface Tracking from Monocular Video

Marc Habermann, Weipeng Xu, Helge Rhodin +3

We propose an efficient method for non-rigid surface tracking from monocular RGB videos. Given a video and a template mesh, our algorithm sequentially registers the template non-ri…

cs.CV2021

TriPose: A Weakly-Supervised 3D Human Pose Estimation via Triangulation from Video

Mohsen Gholami, Ahmad Rezaei, Helge Rhodin +2

Estimating 3D human poses from video is a challenging problem. The lack of 3D human pose annotations is a major obstacle for supervised training and for generalization to unseen da…