Hexplane: A fast representation for dynamic scenes

A Cao, J Johnson - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …

Scaffold-gs: Structured 3d gaussians for view-adaptive rendering

T Lu, M Yu, L Xu, Y Xiangli, L Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Neural rendering methods have significantly advanced photo-realistic 3D scene rendering
in various academic and industrial applications. The recent 3D Gaussian Splatting method …

Neurbf: A neural fields representation with adaptive radial basis functions

Z Chen, Z Li, L Song, L Chen, J Yu… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present a novel type of neural fields that uses general radial bases for signal
representation. State-of-the-art neural fields typically rely on grid-based representations for …

Dynmf: Neural motion factorization for real-time dynamic view synthesis with 3d gaussian splatting

A Kratimenos, J Lei, K Daniilidis - European Conference on Computer …, 2025 - Springer
Accurately and efficiently modeling dynamic scenes and motions is considered so
challenging a task due to temporal dynamics and motion complexity. To address these …

Strivec: Sparse tri-vector radiance fields

Q Gao, Q Xu, H Su, U Neumann… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
We propose Strivec, a novel neural representation that models a 3D scene as a radiance
field with sparsely distributed and compactly factorized local tensor feature grids. Our …

Tetra-nerf: Representing neural radiance fields using tetrahedra

J Kulhanek, T Sattler - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Abstract Neural Radiance Fields (NeRFs) are a very recent and very popular approach for
the problems of novel view synthesis and 3D reconstruction. A popular scene representation …

Gs-lrm: Large reconstruction model for 3d gaussian splatting

K Zhang, S Bi, H Tan, Y Xiangli, N Zhao… - … on Computer Vision, 2025 - Springer
We propose GS-LRM, a scalable large reconstruction model that can predict high-quality 3D
Gaussian primitives from 2–4 posed sparse images in\(\sim\) 0.23 s on single A100 GPU …

ZeroRF: Fast Sparse View 360deg Reconstruction with Zero Pretraining

R Shi, X Wei, C Wang, H Su - Proceedings of the IEEE/CVF …, 2024 - openaccess.thecvf.com
We present ZeroRF a novel per-scene optimization method addressing the challenge of
sparse view 360deg reconstruction in neural field representations. Current breakthroughs …

3d motion magnification: Visualizing subtle motions from time-varying radiance fields

BY Feng, H Alzayer, M Rubinstein… - Proceedings of the …, 2023 - openaccess.thecvf.com
Motion magnification helps us visualize subtle, imperceptible motion. However, prior
methods only work for 2D videos captured with a fixed camera. We present a 3D motion …

Canonical factors for hybrid neural fields

B Yi, W Zeng, S Buchanan… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Factored feature volumes offer a simple way to build more compact, efficient, and
intepretable neural fields, but also introduce biases that are not necessarily beneficial for …