papers

Publications (7)

cs.CV2022

Scaling Neural Face Synthesis to High FPS and Low Latency by Neural Caching

Frank Yu, Sid Fels, Helge Rhodin

Recent neural rendering approaches greatly improve image quality, reaching near photorealism. However, the underlying neural networks have high runtime, precluding telepresence and…

cs.CV2021

PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

Frank Yu, Mathieu Salzmann, Pascal Fua +1

Local processing is an essential feature of CNNs and other neural network architectures - it is one of the reasons why they work so well on images where relevant information is, to…

cs.CV2025

SqueezeMe: Mobile-Ready Distillation of Gaussian Full-Body Avatars

Forrest Iandola, Stanislav Pidhorskyi, Igor Santesteban +7

Gaussian-based human avatars have achieved an unprecedented level of visual fidelity. However, existing approaches based on high-capacity neural networks typically require a deskto…

cs.OH2012

BigFoot: Analysis, monitoring, tracking and sharing of bio-medical features of human appendages using consumer-grade home and office based imaging devices

Sam Mavandadi, Steve Feng, Frank Yu +2

Here we describe a system for personal and professional management and analysis of bio-medical images captured using off-the-shelf, consumer-grade imaging devices such as scanners,…

cs.SD2025

BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models

Susan Liang, Dejan Markovic, Israel D. Gebru +7

Binaural rendering aims to synthesize binaural audio that mimics natural hearing based on a mono audio and the locations of the speaker and listener. Although many methods have bee…

cs.CV2021

A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose

Shih-Yang Su, Frank Yu, Michael Zollhoefer +1

While deep learning reshaped the classical motion capture pipeline with feed-forward networks, generative models are required to recover fine alignment via iterative refinement. Un…

cs.CV2020

Few-shot Scene-adaptive Anomaly Detection

Yiwei Lu, Frank Yu, Mahesh Kumar Krishna Reddy +1

We address the problem of anomaly detection in videos. The goal is to identify unusual behaviours automatically by learning exclusively from normal videos. Most existing approaches…