activity
20182025
most citedConvolutional Autoencoders for Human Motion Infilling

88 citations · 423 across the 74 of their papers we have counts for

collaborators

89 papers

cs.CV2025★ 2 cited

WorldPose: A World Cup Dataset for Global 3D Human Pose Estimation

Tianjian Jiang, Johsan Billingham, Sebastian Müksch +7

We present WorldPose, a novel dataset for advancing research in multi-person global pose estimation in the wild, featuring footage from the 2022 FIFA World Cup. While previous data…

cs.CV2025

Regressor-Guided Image Editing Shifts Emotion and Disengagement Timing in Social Media

Christoph Gebhardt, Robin Willardt, Seyedmorteza Sadat +5

Internet overuse is a widespread phenomenon in today's digital society. Existing interventions, such as time limits or grayscaling, often rely on restrictive controls that provoke…

cs.LG2024

Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models

Seyedmorteza Sadat, Otmar Hilliges, Romann M. Weber

Classifier-free guidance (CFG) is crucial for improving both generation quality and alignment between the input condition and final output in diffusion models. While a high guidanc…

cs.CV2024★ 14 cited

Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures

Marcel C. Bühler, Gengyan Li, Erroll Wood +13

Volumetric modeling and neural radiance field representations have revolutionized 3D face capture and photorealistic novel view synthesis. However, these methods often require hund…

cs.CV2024

ReLoo: Reconstructing Humans Dressed in Loose Garments from Monocular Video in the Wild

Chen Guo, Tianjian Jiang, Manuel Kaufmann +4

While previous years have seen great progress in the 3D reconstruction of humans from monocular videos, few of the state-of-the-art methods are able to handle loose garments that e…

cs.CV2024

Human Hair Reconstruction with Strand-Aligned 3D Gaussians

Egor Zakharov, Vanessa Sklyarova, Michael Black +3

We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions fr…

cs.CV2024

Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photorealistic Appearance from Multi-View Video

Boxiang Rong, Artur Grigorev, Wenbo Wang +4

We introduce Gaussian Garments, a novel approach for reconstructing realistic simulation-ready garment assets from multi-view videos. Our method represents garments with a combinat…

cs.CV2024

AvatarPose: Avatar-guided 3D Pose Estimation of Close Human Interaction from Sparse Multi-view Videos

Feichi Lu, Zijian Dong, Jie Song +1

Despite progress in human motion capture, existing multi-view methods often face challenges in estimating the 3D pose and shape of multiple closely interacting people. This difficu…

cs.LG2024

No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Seyedmorteza Sadat, Manuel Kansy, Otmar Hilliges +1

Classifier-free guidance (CFG) has become the standard method for enhancing the quality of conditional diffusion models. However, employing CFG requires either training an uncondit…

cs.CV2024★ 1 cited

MultiPly: Reconstruction of Multiple People from Monocular Video in the Wild

Zeren Jiang, Chen Guo, Manuel Kaufmann +4

We present MultiPly, a novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos. Reconstructing multiple individuals moving and interacting naturally…

cs.CV2024

EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting

Daiwei Zhang, Gengyan Li, Jiajie Li +5

Human activities are inherently complex, often involving numerous object interactions. To better understand these activities, it is crucial to model their interactions with the env…

cs.LG2024

RILe: Reinforced Imitation Learning

Mert Albaba, Sammy Christen, Thomas Langarek +3

Acquiring complex behaviors is essential for artificially intelligent agents, yet learning these behaviors in high-dimensional settings poses a significant challenge due to the vas…

cs.GR2024★ 25 cited

ContourCraft: Learning to Resolve Intersections in Neural Multi-Garment Simulations

Artur Grigorev, Giorgio Becherini, Michael J. Black +2

Learning-based approaches to cloth simulation have started to show their potential in recent years. However, handling collisions and intersections in neural simulations remains a l…

cs.LG2024★ 1 cited

LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models

Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley +2

Advances in latent diffusion models (LDMs) have revolutionized high-resolution image generation, but the design space of the autoencoder that is central to these systems remains un…

cs.CV2024

4D-DRESS: A 4D Dataset of Real-world Human Clothing with Semantic Annotations

Wenbo Wang, Hsuan-I Ho, Chen Guo +5

The studies of human clothing for digital avatars have predominantly relied on synthetic datasets. While easy to collect, synthetic data often fall short in realism and fail to cap…

cs.CV2024★ 1 cited

WANDR: Intention-guided Human Motion Generation

Markos Diomataris, Nikos Athanasiou, Omid Taheri +3

Synthesizing natural human motions that enable a 3D human avatar to walk and reach for arbitrary goals in 3D space remains an unsolved problem with many applications. Existing meth…

cs.RO2024★ 1 cited

GraspXL: Generating Grasping Motions for Diverse Objects at Scale

Hui Zhang, Sammy Christen, Zicong Fan +2

Human hands possess the dexterity to interact with diverse objects such as grasping specific parts of the objects and/or approaching them from desired directions. More importantly,…

cs.CV2024★ 2 cited

Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects

Zicong Fan, Takehiko Ohkawa, Linlin Yang +21

We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic 3Dunderstanding of such interactions from egocentric views is important fo…

cs.CV2024★ 2 cited

RHOBIN Challenge: Reconstruction of Human Object Interaction

Xianghui Xie, Xi Wang, Nikos Athanasiou +17

Modeling the interaction between humans and objects has been an emerging research direction in recent years. Capturing human-object interaction is however a very challenging task d…

cs.CV2023★ 2 cited

HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles

Vanessa Sklyarova, Egor Zakharov, Otmar Hilliges +2

We present HAAR, a new strand-based generative model for 3D human hairstyles. Specifically, based on textual inputs, HAAR produces 3D hairstyles that could be used as production-le…

cs.CV2023

Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction

M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel +5

Understanding drivers' decision-making is crucial for road safety. Although predicting the ego-vehicle's path is valuable for driver-assistance systems, existing methods mainly foc…

cs.CV2023★ 1 cited

HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video

Zicong Fan, Maria Parelli, Maria Eleni Kadoglou +4

Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour. However, most existing met…

cs.CV2023★ 1 cited

PALM: Predicting Actions through Language Models

Sanghwan Kim, Daoji Huang, Yongqin Xian +3

Understanding human activity is a crucial yet intricate task in egocentric vision, a field that focuses on capturing visual perspectives from the camera wearer's viewpoint. Traditi…

cs.CV2023★ 1 cited

A Unified Approach for Text- and Image-guided 4D Scene Generation

Yufeng Zheng, Xueting Li, Koki Nagano +4

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of t…