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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.CV2026

Reflecting Process Expertise in Procedural Material Generation

Kunal Gupta, Gaurav Joshi, Yen-Ru Chen +3

The paper introduces a method that captures expert material‑creation workflows as textual process traces and uses large language models to generate and compile these traces into ed…

cs.CV2026

-Scene: Physically Grounded Image-to-3D Scene Reconstruction

Haodong Li, Lulu Shao, Haolin Lu +4

Reconstructing compositional 3D scenes from a single image is a fundamental challenge in 3D world modeling. Recent methods can recover high-fidelity, complete 3D objects and predic…

cs.GR2026

Generative Blocks World: Moving Things Around in Pictures

Vaibhav Vavilala, Seemandhar Jain, Rahul Vasanth +2

We describe Generative Blocks World to interact with the scene of a generated image by manipulating simple geometric abstractions. Our method represents scenes as assemblies of con…

cs.CV2026

Improved Convex Decomposition with Ensembling and Negative Primitives

Vaibhav Vavilala, Florian Kluger, Seemandhar Jain +3

Describing a scene in terms of primitives -- geometrically simple shapes that offer a parsimonious but accurate abstraction of structure -- is an established and difficult fitting…

cs.CV2026

NERFIFY: A Multi-Agent Framework for Turning NeRF Papers into Code

Seemandhar Jain, Keshav Gupta, Kunal Gupta +1

The proliferation of neural radiance field (NeRF) research requires significant efforts to reimplement papers before building upon them. We introduce NERFIFY, a multi-agent framewo…

cs.CV2025

Latent Intrinsics Emerge from Training to Relight

Xiao Zhang, William Gao, Seemandhar Jain +3

Image relighting is the task of showing what a scene from a source image would look like if illuminated differently. Inverse graphics schemes recover an explicit representation of…