88 citations · 423 across the 74 of their papers we have counts for
17 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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,…
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…
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…