Results 21 to 30 of about 3,318,906 (295)
Federated Neural Radiance Fields
CoRR, 2023 10 pages, 7 ...
Lachlan Holden +3 more
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Convolutional Neural Opacity Radiance Fields [PDF]
2021 IEEE International Conference on Computational Photography (ICCP), 2021 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 brightness, color. In this paper, we propose a novel scheme to generate opacity radiance fields with a convolutional neural renderer for fuzzy objects, which is the first to ...
Haimin Luo +6 more
openaire +4 more sources
EfficientNeRF - Efficient Neural Radiance Fields
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes. It takes long per-scene training time and per-image testing time. In this paper, we present EfficientNeRF as an efficient NeRF-based method to represent 3D scene and synthesize novel-view images.
Tao Hu 0011 +4 more
openaire +3 more sources
Nerfies: Deformable Neural Radiance Fields [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural radiance fields (NeRF) by optimizing an additional continuous volumetric deformation field that warps each observed point into a canonical 5D NeRF.
Keunhong Park +6 more
openaire +2 more sources
SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learning [PDF]
, 2023 As previous representations for reinforcement learning cannot effectively incorporate a human-intuitive understanding of the 3D environment, they usually suffer from sub-optimal performances.
Lee, Seungjae +2 more
core +1 more source
MarkNerf:Watermarking for Neural Radiance Field
CoRR, 2023 A watermarking algorithm is proposed in this paper to address the copyright protection issue of implicit 3D models. The algorithm involves embedding watermarks into the images in the training set through an embedding network, and subsequently utilizing the NeRF model for 3D modeling.
Lifeng Chen +5 more
openaire +3 more sources
Self-Calibrating Neural Radiance Fields [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Accepted in ICCV21, Project Page: https://postech-cvlab.github.io/SCNeRF/
Jeong, Yoonwoo +5 more
openaire +5 more sources
MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields
IEEE Access, 2023 We present MMNeRF, a simple yet powerful learning framework for highly photo-realistic novel view synthesis by learning Multi-modal and Multi-view features to guide neural radiance fields to a generic model.
Qi Zhang +3 more
doaj +1 more source
Remote Sensing Neural Radiance Fields for Multi-View Satellite Photogrammetry
Remote Sensing, 2023 Neural radiance fields (NeRFs) combining machine learning with differentiable rendering have arisen as one of the most promising approaches for novel view synthesis and depth estimates.
Songlin Xie +3 more
doaj +1 more source
Steganography for Neural Radiance Fields by Backdooring
CoRR, 2023 The utilization of implicit representation for visual data (such as images, videos, and 3D models) has recently gained significant attention in computer vision research. In this letter, we propose a novel model steganography scheme with implicit neural representation.
Weina Dong +5 more
openaire +3 more sources