80 citations · 108 across the 22 of their papers we have counts for
22 papers · 1 filter
ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation
Sihan Ren, Gaozheng Li, Yuanshang Quan +5
Simultaneous Sign Language Translation (SLT) is critical for real-time communication, yet existing methods remain largely confined to sentence-level, offline settings that assume p…
EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs
Jiameng Li, Minye Wu, Jiezhang Cao +2
Long-form video understanding remains challenging for Video Large Language Models (VideoLLMs), as the dense frame sampling introduces massive visual tokens while sparse sampling ri…
V^3: Viewing Volumetric Videos on Mobiles via Streamable 2D Dynamic Gaussians
Penghao Wang, Zhirui Zhang, Liao Wang +5
Experiencing high-fidelity volumetric video as seamlessly as 2D videos is a long-held dream. However, current dynamic 3DGS methods, despite their high rendering quality, face chall…
Implicit Gaussian Splatting with Efficient Multi-Level Tri-Plane Representation
Minye Wu, Tinne Tuytelaars
Recent advancements in photo-realistic novel view synthesis have been significantly driven by Gaussian Splatting (3DGS). Nevertheless, the explicit nature of 3DGS data entails cons…
Unveiling the Ambiguity in Neural Inverse Rendering: A Parameter Compensation Analysis
Georgios Kouros, Minye Wu, Sushruth Nagesh +2
Inverse rendering aims to reconstruct the scene properties of objects solely from multiview images. However, it is an ill-posed problem prone to producing ambiguous estimations dev…
TeTriRF: Temporal Tri-Plane Radiance Fields for Efficient Free-Viewpoint Video
Minye Wu, Zehao Wang, Georgios Kouros +1
Neural Radiance Fields (NeRF) revolutionize the realm of visual media by providing photorealistic Free-Viewpoint Video (FVV) experiences, offering viewers unparalleled immersion an…
NeVRF: Neural Video-based Radiance Fields for Long-duration Sequences
Minye Wu, Tinne Tuytelaars
Adopting Neural Radiance Fields (NeRF) to long-duration dynamic sequences has been challenging. Existing methods struggle to balance between quality and storage size and encounter…
VideoRF: Rendering Dynamic Radiance Fields as 2D Feature Video Streams
Liao Wang, Kaixin Yao, Chengcheng Guo +5
Neural Radiance Fields (NeRFs) excel in photorealistically rendering static scenes. However, rendering dynamic, long-duration radiance fields on ubiquitous devices remains challeng…
Ref-DVGO: Reflection-Aware Direct Voxel Grid Optimization for an Improved Quality-Efficiency Trade-Off in Reflective Scene Reconstruction
Georgios Kouros, Minye Wu, Shubham Shrivastava +3
Neural Radiance Fields (NeRFs) have revolutionized the field of novel view synthesis, demonstrating remarkable performance. However, the modeling and rendering of reflective object…
Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos
Liao Wang, Qiang Hu, Qihan He +5
The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that util…
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions
Yuheng Jiang, Suyi Jiang, Guoxing Sun +5
4D modeling of human-object interactions is critical for numerous applications. However, efficient volumetric capture and rendering of complex interaction scenarios, especially fro…
Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time
Liao Wang, Jiakai Zhang, Xinhang Liu +6
Implicit neural representations such as Neural Radiance Field (NeRF) have focused mainly on modeling static objects captured under multi-view settings where real-time rendering can…
iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering
Liao Wang, Ziyu Wang, Pei Lin +5
Generating ``bullet-time'' effects of human free-viewpoint videos is critical for immersive visual effects and VR/AR experience. Recent neural advances still lack the controllable…
Neural Relighting and Expression Transfer On Video Portraits
Youjia Wang, Taotao Zhou, Minzhang Li +4
Photo-realistic video portrait reenactment benefits virtual production and numerous VR/AR experiences. The task remains challenging as the reenacted expression should match the sou…
Few-shot Neural Human Performance Rendering from Sparse RGBD Videos
Anqi Pang, Xin Chen, Haimin Luo +3
Recent neural rendering approaches for human activities achieve remarkable view synthesis results, but still rely on dense input views or dense training with all the capture frames…
PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
Yuwei Li, Minye Wu, Yuyao Zhang +2
Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling…
MirrorNeRF: One-shot Neural Portrait Radiance Field from Multi-mirror Catadioptric Imaging
Ziyu Wang, Liao Wang, Fuqiang Zhao +3
Photo-realistic neural reconstruction and rendering of the human portrait are critical for numerous VR/AR applications. Still, existing solutions inherently rely on multi-view capt…
Editable Free-viewpoint Video Using a Layered Neural Representation
Jiakai Zhang, Xinhang Liu, Xinyi Ye +6
Generating free-viewpoint videos is critical for immersive VR/AR experience but recent neural advances still lack the editing ability to manipulate the visual perception for large…
Convolutional Neural Opacity Radiance Fields
Haimin Luo, Anpei Chen, Qixuan Zhang +4
Photo-realistic modeling and rendering of fuzzy objects with complex opacity are critical for numerous immersive VR/AR applications, but it suffers from strong view-dependent brigh…
Neural Video Portrait Relighting in Real-time via Consistency Modeling
Longwen Zhang, Qixuan Zhang, Minye Wu +2
Video portraits relighting is critical in user-facing human photography, especially for immersive VR/AR experience. Recent advances still fail to recover consistent relit result un…
NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras
Xin Suo, Yuheng Jiang, Pei Lin +4
4D reconstruction and rendering of human activities is critical for immersive VR/AR experience.Recent advances still fail to recover fine geometry and texture results with the leve…
GNeRF: GAN-based Neural Radiance Field without Posed Camera
Quan Meng, Anpei Chen, Haimin Luo +5
We introduce GNeRF, a framework to marry Generative Adversarial Networks (GAN) with Neural Radiance Field (NeRF) reconstruction for the complex scenarios with unknown and even rand…