by America Ortiz | May 31, 2026 | Video Processing, Visual Computing
RenderFlow: Single-Step Neural Rendering via Flow Matching In this paper, we propose a novel, end-to-end, deterministic, single-step neural rendering framework, RenderFlow, built upon a flow matching paradigm. To further strengthen both rendering quality and...
by America Ortiz | May 31, 2026 | Video Processing, Visual Computing
Efficient All-Pairs Correlation Volume Sampling for Optical Flow Estimation In this paper, we propose an algorithm for both memory and compute-efficient implementation of the all-pairs correlation volume sampling, still matching the exact mathematical operator as...
by America Ortiz | May 31, 2026 | Video Processing, Visual Computing
Guardians of the Hair: Rescuing Soft Boundaries in Depth, Stereo, and Novel Views In this paper, we propose a novel data curation pipeline that leverages image matting datasets for training and design a depth fixer network to automatically identify soft boundary...
by America Ortiz | May 31, 2026 | Capture, VFX, Visual Computing
RelightAnyone: A Generalized Relightable 3D Gaussian Head Model In this work, we propose a new generalized relightable 3D Gaussian head model that can relight any subject observed in a single- or multi-view images without requiring OLAT data for that subject. May 31,...
by America Ortiz | Apr 22, 2026 | Machine Learning, Video Processing, Visual Computing
HIGS: History-Guided Sampling for Diffusion Models In this work, we propose a novel momentum-based sampling technique, termed history-guided sampling (HiGS), which enhances quality and efficiency of diffusion sampling by integrating recent model predictions into each...
