Neural operators for accelerating scientific simulations and design
Scientific discovery and engineering design are currently limited by the time and cost of
physical experiments. Numerical simulations are an alternative approach but are usually …
physical experiments. Numerical simulations are an alternative approach but are usually …
Nerf-det: Learning geometry-aware volumetric representation for multi-view 3d object detection
Abstract We present NeRF-Det, a novel method for indoor 3D detection with posed RGB
images as input. Unlike existing indoor 3D detection methods that struggle to model scene …
images as input. Unlike existing indoor 3D detection methods that struggle to model scene …
Nerf-mae: Masked autoencoders for self-supervised 3d representation learning for neural radiance fields
Neural fields excel in computer vision and robotics due to their ability to understand the 3D
visual world such as inferring semantics, geometry, and dynamics. Given the capabilities of …
visual world such as inferring semantics, geometry, and dynamics. Given the capabilities of …
Learning neural duplex radiance fields for real-time view synthesis
Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual
quality. However, to render photorealistic images, NeRFs require hundreds of deep …
quality. However, to render photorealistic images, NeRFs require hundreds of deep …
Binary radiance fields
In this paper, we propose binary radiance fields (BiRF), a storage-efficient radiance field
representation employing binary feature encoding that encodes local features using binary …
representation employing binary feature encoding that encodes local features using binary …
Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive Review
TAQ Nguyen, A Bourki, M Macudzinski… - arXiv preprint arXiv …, 2024 - arxiv.org
This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields
Advances in neural fields are enabling high-fidelity capture of the shape and appearance of
dynamic 3D scenes. However their capabilities lag behind those offered by conventional …
dynamic 3D scenes. However their capabilities lag behind those offered by conventional …
Pick-or-Mix: Dynamic Channel Sampling for ConvNets
Channel pruning approaches for convolutional neural networks (ConvNets) deactivate the
channels statically or dynamically and require special implementation. In addition channel …
channels statically or dynamically and require special implementation. In addition channel …
Cawa-nerf: Instant learning of compression-aware nerf features
Modeling 3D scenes by volumetric features is one of the promising directions of neural
approximations to improve Neural Radiance Field (NeRF) models. Instant-NGP (INGP) …
approximations to improve Neural Radiance Field (NeRF) models. Instant-NGP (INGP) …
Gaussian-det: Learning closed-surface gaussians for 3d object detection
Skins wrapping around our bodies, leathers covering over the sofa, sheet metal coating the
car-it suggests that objects are enclosed by a series of continuous surfaces, which provides …
car-it suggests that objects are enclosed by a series of continuous surfaces, which provides …