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
Towards More Accurate Fake Detection on Images Generated from Advanced Generative and Neural Rendering Models
Chengdong Dong, Vijayakumar Bhagavatula, Zhenyu Zhou, Ajay Kumar
MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields Representation
Peng Wang, Lingzhe Zhao, Yin Zhang, Shiyu Zhao, Peidong Liu
CAD-NeRF: Learning NeRFs from Uncalibrated Few-view Images by CAD Model Retrieval
Xin Wen, Xuening Zhu, Renjiao Yi, Zhifeng Wang, Chenyang Zhu, Kai Xu
Exploring Seasonal Variability in the Context of Neural Radiance Fields for 3D Reconstruction on Satellite Imagery
Liv Kåreborn, Erica Ingerstad, Amanda Berg, Justus Karlsson, Leif Haglund
NeRF-Aug: Data Augmentation for Robotics with Neural Radiance Fields
Eric Zhu, Mara Levy, Matthew Gwilliam, Abhinav Shrivastava
GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes
Gaochao Song, Chong Cheng, Hao Wang
A Probabilistic Formulation of LiDAR Mapping with Neural Radiance Fields
Matthew McDermott, Jason Rife
Content-Aware Radiance Fields: Aligning Model Complexity with Scene Intricacy Through Learned Bitwidth Quantization
Weihang Liu, Xue Xian Zheng, Jingyi Yu, Xin Lou
Evaluation of strategies for efficient rate-distortion NeRF streaming
Pedro Martin, António Rodrigues, João Ascenso, Maria Paula Queluz
ST-NeRP: Spatial-Temporal Neural Representation Learning with Prior Embedding for Patient-specific Imaging Study
Liang Qiu, Liyue Shen, Lianli Liu, Junyan Liu, Yizheng Chen, Lei Xing
E-3DGS: Gaussian Splatting with Exposure and Motion Events
Xiaoting Yin, Hao Shi, Yuhan Bao, Zhenshan Bing, Yiyi Liao, Kailun Yang, Kaiwei Wang
Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies
Shrey Vishen, Jatin Sarabu, Chinmay Bharathulwar, Rithwick Lakshmanan, Vishnu Srinivas