21 citations · 62 across the 10 of their papers we have counts for
12 papers · 1 filter
OmnimatteRF: Robust Omnimatte with 3D Background Modeling
Geng Lin, Chen Gao, Jia-Bin Huang +4
Video matting has broad applications, from adding interesting effects to casually captured movies to assisting video production professionals. Matting with associated effects such…
Consistent View Synthesis with Pose-Guided Diffusion Models
Hung-Yu Tseng, Qinbo Li, Changil Kim +3
Novel view synthesis from a single image has been a cornerstone problem for many Virtual Reality applications that provide immersive experiences. However, most existing techniques…
Progressively Optimized Local Radiance Fields for Robust View Synthesis
Andreas Meuleman, Yu-Lun Liu, Chen Gao +4
We present an algorithm for reconstructing the radiance field of a large-scale scene from a single casually captured video. The task poses two core challenges. First, most existing…
Robust Dynamic Radiance Fields
Yu-Lun Liu, Chen Gao, Andreas Meuleman +6
Dynamic radiance field reconstruction methods aim to model the time-varying structure and appearance of a dynamic scene. Existing methods, however, assume that accurate camera pose…
HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling
Benjamin Attal, Jia-Bin Huang, Christian Richardt +4
Volumetric scene representations enable photorealistic view synthesis for static scenes and form the basis of several existing 6-DoF video techniques. However, the volume rendering…
AMICO: Amodal Instance Composition
Peiye Zhuang, Jia-bin Huang, Ayush Saraf +3
Image composition aims to blend multiple objects to form a harmonized image. Existing approaches often assume precisely segmented and intact objects. Such assumptions, however, are…
Learning Neural Light Fields with Ray-Space Embedding Networks
Benjamin Attal, Jia-Bin Huang, Michael Zollhoefer +2
Neural radiance fields (NeRFs) produce state-of-the-art view synthesis results. However, they are slow to render, requiring hundreds of network evaluations per pixel to approximate…
TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis
Benjamin Attal, Eliot Laidlaw, Aaron Gokaslan +4
Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular vid…
Space-time Neural Irradiance Fields for Free-Viewpoint Video
Wenqi Xian, Jia-Bin Huang, Johannes Kopf +1
We present a method that learns a spatiotemporal neural irradiance field for dynamic scenes from a single video. Our learned representation enables free-viewpoint rendering of the…
Speech2Face: Learning the Face Behind a Voice
Tae-Hyun Oh, Tali Dekel, Changil Kim +4
How much can we infer about a person's looks from the way they speak? In this paper, we study the task of reconstructing a facial image of a person from a short audio recording of…
On Learning Associations of Faces and Voices
Changil Kim, Hijung Valentina Shin, Tae-Hyun Oh +3
In this paper, we study the associations between human faces and voices. Audiovisual integration, specifically the integration of facial and vocal information is a well-researched…
Learning-based Video Motion Magnification
Tae-Hyun Oh, Ronnachai Jaroensri, Changil Kim +4
Video motion magnification techniques allow us to see small motions previously invisible to the naked eyes, such as those of vibrating airplane wings, or swaying buildings under th…