activity
20172025
most citedPCPNET: Learning Local Shape Properties from Raw Point Clouds

372 citations · 379 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2025

InstanceGen: Image Generation with Instance-level Instructions

Etai Sella, Yanir Kleiman, Hadar Averbuch-Elor

Despite rapid advancements in the capabilities of generative models, pretrained text-to-image models still struggle in capturing the semantics conveyed by complex prompts that comp…

cs.CV2024★ 1 cited

Meta 3D Gen

Raphael Bensadoun, Tom Monnier, Yanir Kleiman +17

We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3…

cs.CV2024★ 3 cited

Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials

Yawar Siddiqui, Tom Monnier, Filippos Kokkinos +8

We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared…

cs.CV2024★ 3 cited

Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects

Raphael Bensadoun, Yanir Kleiman, Idan Azuri +4

The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and…

cs.CV2023

Replay: Multi-modal Multi-view Acted Videos for Casual Holography

Roman Shapovalov, Yanir Kleiman, Ignacio Rocco +6

We introduce Replay, a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with…

cs.GR2017

Robust Structure-based Shape Correspondence

Yanir Kleiman, Maks Ovsjanikov

We present a robust method to find region-level correspondences between shapes, which are invariant to changes in geometry and applicable across multiple shape representations. We…

cs.CG2017★ 372 cited

PCPNET: Learning Local Shape Properties from Raw Point Clouds

Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov +1

In this paper, we propose PCPNet, a deep-learning based approach for estimating local 3D shape properties in point clouds. In contrast to the majority of prior techniques that conc…

cs.CV2017

Bundle Optimization for Multi-aspect Embedding

Qiong Zeng, Baoquan Chen, Yanir Kleiman +2

Understanding semantic similarity among images is the core of a wide range of computer vision applications. An important step towards this goal is to collect and learn human percep…