Neural Radiance Field
Neural Radiance Fields (NeRFs) are a powerful technique for creating realistic 3D scene representations from 2D images, aiming to reconstruct both geometry and appearance. Current research focuses on improving efficiency and robustness, exploring variations like Gaussian splatting for faster rendering and adapting NeRFs for diverse data modalities (LiDAR, infrared, ultrasound) and challenging conditions (low light, sparse views). This technology has significant implications for various fields, including autonomous driving, robotics, medical imaging, and virtual/augmented reality, by enabling high-fidelity 3D scene modeling and novel view synthesis from limited input data.
Papers
Learning a Diffusion Prior for NeRFs
Guandao Yang, Abhijit Kundu, Leonidas J. Guibas, Jonathan T. Barron, Ben Poole
Combining HoloLens with Instant-NeRFs: Advanced Real-Time 3D Mobile Mapping
Dennis Haitz, Boris Jutzi, Markus Ulrich, Miriam Jaeger, Patrick Huebner
Compositional 3D Human-Object Neural Animation
Zhi Hou, Baosheng Yu, Dacheng Tao
ContraNeRF: 3D-Aware Generative Model via Contrastive Learning with Unsupervised Implicit Pose Embedding
Mijeong Kim, Hyunjoon Lee, Bohyung Han
TextMesh: Generation of Realistic 3D Meshes From Text Prompts
Christina Tsalicoglou, Fabian Manhardt, Alessio Tonioni, Michael Niemeyer, Federico Tombari
HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video
Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang, Eric Zhongcong Xu, Jussi Keppo, Ying Shan, Xiaohu Qie, Mike Zheng Shou
A Comparative Neural Radiance Field (NeRF) 3D Analysis of Camera Poses from HoloLens Trajectories and Structure from Motion
Miriam Jäger, Patrick Hübner, Dennis Haitz, Boris Jutzi
Learning Neural Duplex Radiance Fields for Real-Time View Synthesis
Ziyu Wan, Christian Richardt, Aljaž Božič, Chao Li, Vijay Rengarajan, Seonghyeon Nam, Xiaoyu Xiang, Tuotuo Li, Bo Zhu, Rakesh Ranjan, Jing Liao
Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFs
Frederik Warburg, Ethan Weber, Matthew Tancik, Aleksander Holynski, Angjoo Kanazawa
ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
Marco Toschi, Riccardo De Matteo, Riccardo Spezialetti, Daniele De Gregorio, Luigi Di Stefano, Samuele Salti
LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields
Tang Tao, Longfei Gao, Guangrun Wang, Yixing Lao, Peng Chen, Hengshuang Zhao, Dayang Hao, Xiaodan Liang, Mathieu Salzmann, Kaicheng Yu
Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering
Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong