25 citations · 67 across the 62 of their papers we have counts for
32 papers · 1 filter
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…
Advances in Feed-Forward 3D Reconstruction and View Synthesis: A Survey
Jiahui Zhang, Yuelei Li, Anpei Chen +15
3D reconstruction and view synthesis are foundational problems in computer vision, graphics, and immersive technologies such as augmented reality (AR), virtual reality (VR), and di…
DuetGen: Music Driven Two-Person Dance Generation via Hierarchical Masked Modeling
Anindita Ghosh, Bing Zhou, Rishabh Dabral +5
We present DuetGen, a novel framework for generating interactive two-person dances from music. The key challenge of this task lies in the inherent complexities of two-person dance…
Restereo: Diffusion stereo video generation and restoration
Xingchang Huang, Ashish Kumar Singh, Florian Dubost +6
Stereo video generation has been gaining increasing attention with recent advancements in video diffusion models. However, most existing methods focus on generating 3D stereoscopic…
Do It Yourself: Learning Semantic Correspondence from Pseudo-Labels
Olaf Dünkel, Thomas Wimmer, Christian Theobalt +2
Finding correspondences between semantically similar points across images and object instances is one of the everlasting challenges in computer vision. While large pre-trained visi…
UMA: Ultra-detailed Human Avatars via Multi-level Surface Alignment
Heming Zhu, Guoxing Sun, Christian Theobalt +1
Learning an animatable and clothed human avatar model with vivid dynamics and photorealistic appearance from multi-view videos is an important foundational research problem in comp…
EVA: Expressive Virtual Avatars from Multi-view Videos
Hendrik Junkawitsch, Guoxing Sun, Heming Zhu +2
With recent advancements in neural rendering and motion capture algorithms, remarkable progress has been made in photorealistic human avatar modeling, unlocking immense potential f…
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature Space
Leonhard Sommer, Olaf Dünkel, Christian Theobalt +1
3D morphable models (3DMMs) are a powerful tool to represent the possible shapes and appearances of an object category. Given a single test image, 3DMMs can be used to solve variou…
Ego4o: Egocentric Human Motion Capture and Understanding from Multi-Modal Input
Jian Wang, Rishabh Dabral, Diogo Luvizon +4
This work focuses on tracking and understanding human motion using consumer wearable devices, such as VR/AR headsets, smart glasses, cellphones, and smartwatches. These devices pro…
Matrix-free Second-order Optimization of Gaussian Splats with Residual Sampling
Hamza Pehlivan, Andrea Boscolo Camiletto, Lin Geng Foo +2
3D Gaussian Splatting (3DGS) is widely used for novel view synthesis due to its high rendering quality and fast inference time. However, 3DGS predominantly relies on first-order op…