25 citations · 67 across the 62 of their papers we have counts for
75 papers
AvatarDynamizer: From Static to Dynamic Human Avatars via Generative Dynamic Textures
Guoxing Sun, Heming Zhu, Linjie Lyu +3
For full-body avatars, modeling surface dynamics is crucial for overcoming the uncanny valley and achieving perceptual realism. Person-agnostic methods recover static 3D avatars fr…
Generative Relightable Avatars
Kunwar Maheep Singh, Christian Theobalt, Rishabh Dabral
We present Generative Relightable Avatars (GRA), a person-specific method for photorealistic free-view rendering and environment-map relighting of full-body humans. We postulate th…
SOMA: From Surface Observations to Muscle Anatomy
Eduardo Alvarado, Emily Kim, Gerrit Nolte +4
With the growing demand for realistic virtual humans, parametric body models have become a cornerstone of modern medicine, sports, and entertainment applications. However, most of…
Towards Real-World Wearable Motion Reconstruction
Andrea Boscolo Camiletto, Rishabh Dabral, Eduardo Alvarado +3
The modern-day surge in popularity of wearable devices poses a fundamentally unique motion capture problem: reconstructing full-body movement from any set of sensing hardware worn…
EmoteGPT: 3D Human Facial Expressions from Natural Language Descriptions
Haoran Wang, Mohit Mendiratta, Christian Theobalt +1
Precise control of 3D facial expressions from text is crucial for virtual avatars, animation, and human-computer interaction, yet existing text-to-3D methods jointly generate ident…
DCGrasp: Distance-aware Controllable Grasp Generation
Hiroyasu Akada, Jesús Pérez, Emre Aksan +6
Generating 3D hand-object interactions is essential for applications in robotics, XR, and synthetic data generation, where flexible controllability and strong generalization to div…
EmbodMocap: In-the-Wild 4D Human-Scene Reconstruction for Embodied Agents
Wenjia Wang, Liang Pan, Huaijin Pi +8
Human behaviors in the real world naturally encode rich, long-term contextual information that can be leveraged to train embodied agents for perception, understanding, and acting.…
SceMoS: Scene-Aware 3D Human Motion Synthesis by Planning with Geometry-Grounded Tokens
Anindita Ghosh, Vladislav Golyanik, Taku Komura +3
Synthesizing text-driven 3D human motion within realistic scenes requires learning both semantic intent ("walk to the couch") and physical feasibility (e.g., avoiding collisions).…
DInf-Grid: A Neural Differential Equation Solver with Differentiable Feature Grids
Navami Kairanda, Shanthika Naik, Marc Habermann +3
We present a novel differentiable grid-based representation for efficiently solving differential equations (DEs). Widely used architectures for neural solvers, such as sinusoidal n…
OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control
Xilong Zhou, Jianchun Chen, Pramod Rao +7
We introduce OLATverse, a large-scale dataset comprising around 9M images of 765 real-world objects, captured from multiple viewpoints under a diverse set of precisely controlled l…
Relightable Holoported Characters: Capturing and Relighting Dynamic Human Performance from Sparse Views
Kunwar Maheep Singh, Jianchun Chen, Vladislav Golyanik +5
We present Relightable Holoported Characters (RHC), a novel person-specific method for free-view rendering and relighting of full-body and highly dynamic humans solely observed fro…
Towards Reliable Human Evaluations in Gesture Generation: Insights from a Community-Driven State-of-the-Art Benchmark
Rajmund Nagy, Hendric Voss, Thanh Hoang-Minh +18
We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed experimental setups. This leads…
Modeling Turn-Taking with Semantically Informed Gestures
Varsha Suresh, M. Hamza Mughal, Christian Theobalt +1
In conversation, humans use multimodal cues, such as speech, gestures, and gaze, to manage turn-taking. While linguistic and acoustic features are informative, gestures provide com…
Splat the Net: Radiance Fields with Splattable Neural Primitives
Xilong Zhou, Bao-Huy Nguyen, Loïc Magne +3
Radiance fields have emerged as a predominant representation for modeling 3D scene appearance. Neural formulations such as Neural Radiance Fields provide high expressivity but requ…
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)…
Topology-Aware Optimization of Gaussian Primitives for Human-Centric Volumetric Videos
Yuheng Jiang, Chengcheng Guo, Yize Wu +9
Volumetric video is emerging as a key medium for digitizing the dynamic physical world, creating the virtual environments with six degrees of freedom to deliver immersive user expe…
PractiLight: Practical Light Control Using Foundational Diffusion Models
Yotam Erel, Rishabh Dabral, Vladislav Golyanik +2
Light control in generated images is a difficult task, posing specific challenges, spanning over the entire image and frequency spectrum. Most approaches tackle this problem by tra…
GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals
Mohit Mendiratta, Mayur Deshmukh, Kartik Teotia +3
3D Morphable Models (3DMMs) enable controllable facial geometry and expression editing for reconstruction, animation, and AR/VR, but traditional PCA-based mesh models are limited i…
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…
HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesis
Timo Teufel, Pulkit Gera, Xilong Zhou +5
Simultaneous relighting and novel-view rendering of digital human representations is an important yet challenging task with numerous applications. Progress in this area has been si…
Quantum Visual Fields with Neural Amplitude Encoding
Shuteng Wang, Christian Theobalt, Vladislav Golyanik
Quantum Implicit Neural Representations (QINRs) have emerged as a promising paradigm that leverages parametrised quantum circuits to encode and process classical information. Howev…
Physics-based Human Pose Estimation from a Single Moving RGB Camera
Ayce Idil Aytekin, Chuqiao Li, Diogo Luvizon +4
Most monocular and physics-based human pose tracking methods, while achieving state-of-the-art results, suffer from artifacts when the scene does not have a strictly flat ground pl…
Attention (as Discrete-Time Markov) Chains
Yotam Erel, Olaf Dünkel, Rishabh Dabral +3
We introduce a new interpretation of the attention matrix as a discrete-time Markov chain. Our interpretation sheds light on common operations involving attention scores such as se…
CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts
Olaf Dünkel, Artur Jesslen, Jiahao Xie +3
An important challenge when using computer vision models in the real world is to evaluate their performance in potential out-of-distribution (OOD) scenarios. While simple synthetic…