A training-free Spatio-Temporal Attention Chain framework accelerates 4D mesh generation 13x, improves quality, scales to 16x longer videos, and supports downstream tracking and camera estimation.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Encoding user interactions into visual in-context example pairs turns static models into controllable systems that improve IoU, PSNR, and LPIPS on guided tasks without retraining.
citing papers explorer
-
Fast 4D Mesh Generation by Spatio-Temporal Attention Chains
A training-free Spatio-Temporal Attention Chain framework accelerates 4D mesh generation 13x, improves quality, scales to 16x longer videos, and supports downstream tracking and camera estimation.
-
From Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks
Encoding user interactions into visual in-context example pairs turns static models into controllable systems that improve IoU, PSNR, and LPIPS on guided tasks without retraining.