88 citations · 226 across the 15 of their papers we have counts for
22 papers
Diversify Diffusion with Temperature Sampling and Variance-Corrective Time Shifting
Peizhuo Li, Emre Aksan, Alexandru-Eugen Ichim +2
Diffusion models faithfully reproduce their training distribution, but also inherit its imbalances and leave rare or under-represented modes hard to reach. A natural inference-time…
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…
VEPHand: View-Efficient Photometric Hand Performance Capture at Scale
Zhengyang Shen, Kai-Hung Chang, Erroll Wood +18
Robust, high-fidelity 3D hand capture, while fundamental to digital human creation, remains challenging with practical multi-view systems that balance rich photometry with the geom…
ECHO: Ego-Centric modeling of Human-Object interactions
Ilya A. Petrov, Vladimir Guzov, Riccardo Marin +5
Modeling human-object interactions (HOI) from an egocentric perspective is a critical yet challenging task, particularly when relying on sparse signals from wearable devices like s…
Optimizing Diffusion Noise Can Serve As Universal Motion Priors
Korrawe Karunratanakul, Konpat Preechakul, Emre Aksan +3
We propose Diffusion Noise Optimization (DNO), a new method that effectively leverages existing motion diffusion models as motion priors for a wide range of motion-related tasks. I…
Physically Plausible Full-Body Hand-Object Interaction Synthesis
Jona Braun, Sammy Christen, Muhammed Kocabas +2
We propose a physics-based method for synthesizing dexterous hand-object interactions in a full-body setting. While recent advancements have addressed specific facets of human-obje…