Results 31 to 40 of about 171,197 (277)
Neural Relightable Participating Media Rendering
, 2021 Learning neural radiance fields of a scene has recently allowed realistic novel view synthesis of the scene, but they are limited to synthesize images under the original fixed lighting condition. Therefore, they are not flexible for the eagerly desired tasks like relighting, scene editing and scene composition.
Zheng, Q. +2 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
DeepAPT: Nation-State APT Attribution Using End-to-End Deep Neural Networks
, 2017 In recent years numerous advanced malware, aka advanced persistent threats (APT) are allegedly developed by nation-states. The task of attributing an APT to a specific nation-state is extremely challenging for several reasons.
E Stamatatos +6 more
core +1 more source
, 2020 Movie productions use high resolution 3d characters with complex proprietary rigs to create the highest quality images possible for large displays. Unfortunately, these 3d assets are typically not compatible with real-time graphics engines used for games, mixed reality and real-time pre-visualization.
Borer, Dominik +4 more
openaire +2 more sources
Unsupervised Continual Semantic Adaptation Through Neural Rendering
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 An increasing amount of applications rely on data-driven models that are deployed for perception tasks across a sequence of scenes. Due to the mismatch between training and deployment data, adapting the model on the new scenes is often crucial to obtain good performance.
Liu, Zhizheng +5 more
openaire +2 more sources
Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 We present a neural rendering framework that maps a voxelized scene into a high quality image. Highly-textured objects and scene element interactions are realistically rendered by our method, despite having a rough representation as an input. Moreover, our approach allows controllable rendering: geometric and appearance modifications in the input are ...
Rematas, Konstantinos, Ferrari, Vittorio
openaire +2 more sources
Dual-Modality Cross-Interaction-Based Hybrid Full-Frame Video Stabilization
Applied SciencesThis study aims to generate visually useful imagery by preventing cropping while maintaining resolution and minimizing the degradation of stability and distortion to enhance the stability of a video for Augmented Reality applications. The focus is placed
Jaeyoung Jang, Yuseok Ban, Kyungjae Lee
doaj +1 more source
Towards Proving the Adversarial Robustness of Deep Neural Networks
, 2017 Autonomous vehicles are highly complex systems, required to function reliably in a wide variety of situations. Manually crafting software controllers for these vehicles is difficult, but there has been some success in using deep neural networks generated
Barrett, Clark +4 more
core +1 more source
Hybrid mesh-neural representation for 3D transparent object reconstruction
Computational Visual MediaIn this study, we propose a novel method to reconstruct the 3D shapes of transparent objects using images captured by handheld cameras under natural lighting conditions.
Jiamin Xu +3 more
doaj +1 more source
Neural-Augmented Static Analysis of Android Communication
, 2018 We address the problem of discovering communication links between applications in the popular Android mobile operating system, an important problem for security and privacy in Android.
Abadi MartÃn +9 more
core +1 more source