23 citations · 48 across the 9 of their papers we have counts for
12 papers
TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions
Or Perel, Hassan Abu Alhaija, Zian Wang +4
We introduce TRON, a rendering framework that combines 3D Gaussian ray tracing with neural rendering to enable realistic and controllable rendering of real-world 3D scenes under no…
ArtisanGS: Interactive Tools for Gaussian Splat Selection with AI and Human in the Loop
Clement Fuji Tsang, Anita Hu, Or Perel +2
Representation in the family of 3D Gaussian Splats (3DGS) are growing into a viable alternative to traditional graphics for an expanding number of application, including recent tec…
Gaussian See, Gaussian Do: Semantic 3D Motion Transfer from Multiview Video
Yarin Bekor, Gal Michael Harari, Or Perel +1
We present Gaussian See, Gaussian Do, a novel approach for semantic 3D motion transfer from multiview video. Our method enables rig-free, cross-category motion transfer between obj…
3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes
Nicolas Moenne-Loccoz, Ashkan Mirzaei, Or Perel +6
Particle-based representations of radiance fields such as 3D Gaussian Splatting have found great success for reconstructing and re-rendering of complex scenes. Most existing method…
Simplicits: Mesh-Free, Geometry-Agnostic, Elastic Simulation
Vismay Modi, Nicholas Sharp, Or Perel +2
The proliferation of 3D representations, from explicit meshes to implicit neural fields and more, motivates the need for simulators agnostic to representation. We present a data-,…
SKED: Sketch-guided Text-based 3D Editing
Aryan Mikaeili, Or Perel, Mehdi Safaee +2
Text-to-image diffusion models are gradually introduced into computer graphics, recently enabling the development of Text-to-3D pipelines in an open domain. However, for interactiv…
SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation
Amir Hertz, Or Perel, Raja Giryes +2
Neural implicit fields are quickly emerging as an attractive representation for learning based techniques. However, adopting them for 3D shape modeling and editing is challenging.…
Mesh Draping: Parametrization-Free Neural Mesh Transfer
Amir Hertz, Or Perel, Raja Giryes +2
Despite recent advances in geometric modeling, 3D mesh modeling still involves a considerable amount of manual labor by experts. In this paper, we introduce Mesh Draping: a neural…
SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization
Amir Hertz, Or Perel, Raja Giryes +2
Multilayer-perceptrons (MLP) are known to struggle with learning functions of high-frequencies, and in particular cases with wide frequency bands. We present a spatially adaptive p…
Learning Multimodal Affinities for Textual Editing in Images
Or Perel, Oron Anschel, Omri Ben-Eliezer +2
Nowadays, as cameras are rapidly adopted in our daily routine, images of documents are becoming both abundant and prevalent. Unlike natural images that capture physical objects, do…
Can You Read Me Now? Content Aware Rectification using Angle Supervision
Amir Markovitz, Inbal Lavi, Or Perel +2
The ubiquity of smartphone cameras has led to more and more documents being captured by cameras rather than scanned. Unlike flatbed scanners, photographed documents are often folde…
READ: Recursive Autoencoders for Document Layout Generation
Akshay Gadi Patil, Omri Ben-Eliezer, Or Perel +1
Layout is a fundamental component of any graphic design. Creating large varieties of plausible document layouts can be a tedious task, requiring numerous constraints to be satisfie…