Signals 4 · free daily AI digest

Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations

Paper recorded by Signals 4 on 2026-09-03 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04

Category: cs.CV · 计算机视觉 · first seen 2026-09-04

Abstract

3D Foundation Models (3DFMs) such as VGGT have recently pushed the boundaries of 3D vision by predicting rich unified representations with feed-foward transformers. The scene representations learned by these models enable strong performance on multiple 3D vision tasks. In this paper, we investigate using their internal representations to infer 3D in the scene from new views. Our hypothesis is that

Read on arXiv →

#147 most recent of 237 cs.CV papers we have recorded · ↑ newer: Puffin-World: Scaling a Unified Multimodal Model with Native 3D World · ↓ older: Persistent Identity Preservation in Generative Image Models: A Benchma
Cite this page: Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations: the #147 most recent of 237 cs.CV papers we have recorded (as of 2026-09-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/zero-shot-novel-depth-synthesis-using-3d-foundation-models-scene-representations.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.CV papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions