Results 31 to 40 of about 8,361,437 (204)
Instance Neural Radiance Field [PDF]
, 2023 This paper presents one of the first learning-based NeRF 3D instance segmentation pipelines, dubbed as Instance Neural Radiance Field, or Instance-NeRF.
Liu, Yichen +4 more
core +3 more sources
IBL-NeRF: Image-Based Lighting Formulation of Neural Radiance Fields
, 2023 We propose IBL-NeRF, which decomposes the neural radiance fields (NeRF) of large-scale indoor scenes into intrinsic components. Recent approaches further decompose the baked radiance of the implicit volume into intrinsic components such that one can ...
Choi, Changwoon +2 more
core +2 more sources
NERFBK: A HOLISTIC DATASET FOR BENCHMARKING NERF-BASED 3D RECONSTRUCTION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Neural Radiance Field methods are innovative solutions to derive 3D data from a set of oriented images. This paper introduces new real and synthetic image datasets - called NeRFBK - specifically designed for testing and comparing NeRF-based 3D ...
Z. Yan +7 more
doaj +1 more source
SeaThru-NeRF: Neural Radiance Fields in Scattering Media
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Research on neural radiance fields (NeRFs) for novel view generation is exploding with new models and extensions. However, a question that remains unanswered is what happens in underwater or foggy scenes where the medium strongly influences the appearance of objects. Thus far, NeRF and its variants have ignored these cases.
Deborah Levy +6 more
openaire +3 more sources
Reconstructing Continuous Light Field From Single Coded Image
IEEE Access, 2023 We propose a method for reconstructing a continuous light field of a target scene from a single observed image. Our method takes the best of two worlds: joint aperture-exposure coding for compressive light-field acquisition, and a neural radiance field ...
Yuya Ishikawa +3 more
doaj +1 more source
Event-Based Camera Tracker by ∇
IEEE Access, 2023 When a camera travels across a 3D world, only a fraction of pixel value changes; an event-based camera observes the change as sparse events. How can we utilize sparse events for efficient recovery of the camera pose?
Mana Masuda +2 more
doaj +1 more source
NAS-NeRF: Generative Neural Architecture Search for Neural Radiance Fields
CoRR, 2023 Neural radiance fields (NeRFs) enable high-quality novel view synthesis, but their high computational complexity limits deployability. While existing neural-based solutions strive for efficiency, they use one-size-fits-all architectures regardless of scene complexity.
Saeejith Nair +3 more
openaire +2 more sources
Dehazing-NeRF: Neural Radiance Fields from Hazy Images
CoRR, 2023 Neural Radiance Field (NeRF) has received much attention in recent years due to the impressively high quality in 3D scene reconstruction and novel view synthesis. However, image degradation caused by the scattering of atmospheric light and object light by particles in the atmosphere can significantly decrease the reconstruction quality when shooting ...
Tian Li, Lu Li, Wei Wang, Zhangchi Feng
openaire +2 more sources
UP-NeRF: Unconstrained Pose-Prior-Free Neural Radiance Fields
, 2023 Neural Radiance Field (NeRF) has enabled novel view synthesis with high fidelity given images and camera poses.Subsequent works even succeeded in eliminating the necessity of pose priors by jointly optimizing NeRF and camera pose.However, these works are
Choi, Minhyuk +2 more
core +1 more source
Assessment of 3D Model for Photogrammetric Purposes Using AI Tools Based on NeRF Algorithm
Heritage, 2023 The aim of the paper is to analyse the performance of the Neural Radiance Field (NeRF) algorithm, implemented in Instant-NGP software, for photogrammetric purposes.
Massimiliano Pepe +2 more
doaj +1 more source