CANLI
xAI, Imagine API’yi 2.0’a Yükseltmeye Hazırlanıyor: Görüntü ve Video Tek…·Microsoft MAI-Cyber-1-Flash’ı Duyurdu·Moonshot AI, Kimi K3 Model Ağırlıklarını ve Teknik Raporunu Açık…
6 Oct 2026 · 00:35 GMT+3
Ai Haber – Türkiyenin Yapay Zeka Haber Portalı
ARAşTıRMA · BILGISAYARLı GöRü arXiv:2610.03715 2 Eki 2026 · v1

4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes

Ruihong Shen, Žiga Kovačič, Peter Kulits, Xingrui Wang, Zizhang Li, +4 yazar

YAYIN:2 Eki 2026 ALAN:cs.CV OKUMA:10

Özet

We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs. To accomplish this, agents must translate visual observations into compact representations of scene structure and dynamics, by implementing abstractions such as physical simulations to reproduce complex behavior. To evaluate this capability, we curate a set of real-world videos and construct synthetic scenes spanning diverse physical phenomena, including deformation, fluid flow, and fracture. We perform extensive benchmarking of frontier models, finding that strong static reconstruction capabilities do not yet translate into reliable reconstruction of complex dynamics. 4DCodeBench provides a testbed for tracking progress toward agents that can interpret the dynamics of the world through code. Our benchmark is available at https://github.com/4DCodeBench/4DCodeBench

Özetle: We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs.

Özet

We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs. To accomplish this, agents must translate visual observations into compact representations of scene structure and dynamics, by implementing abstractions such as physical simulations to reproduce complex behavior. To evaluate this capability, we curate a set of real-world videos and construct synthetic scenes spanning diverse physical phenomena, including deformation, fluid flow, and fracture. We perform extensive benchmarking of frontier models, finding that strong static reconstruction capabilities do not yet translate into reliable reconstruction of complex dynamics. 4DCodeBench provides a testbed for tracking progress toward agents that can interpret the dynamics of the world through code. Our benchmark is available at https://github.com/4DCodeBench/4DCodeBench

Orijinal Özet (İngilizce)

We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs. To accomplish this, agents must translate visual observations into compact representations of scene structure and dynamics, by implementing abstractions such as physical simulations to reproduce complex behavior. To evaluate this capability, we curate a set of real-world videos and construct synthetic scenes spanning diverse physical phenomena, including deformation, fluid flow, and fracture. We perform extensive benchmarking of frontier models, finding that strong static reconstruction capabilities do not yet translate into reliable reconstruction of complex dynamics. 4DCodeBench provides a testbed for tracking progress toward agents that can interpret the dynamics of the world through code. Our benchmark is available at https://github.com/4DCodeBench/4DCodeBench

Kaynak: arXiv:2610.03715 · PDF

BibTeX

@article{shen2026dcodebench,
  title   = {4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes},
  author  = {Ruihong Shen and Žiga Kovačič and Peter Kulits and Xingrui Wang and Zizhang Li and Joshua B. Tenenbaum and Alan Yuille and Jieneng Chen and Jiajun Wu},
  journal = {arXiv preprint arXiv:2610.03715},
  year    = {2026},
  url     = {https://arxiv.org/abs/2610.03715}
}

Tartışma

Bu habere emoji ile tepki ver

Hizli:

Henüz yorum yok. İlk yorumu siz yapın!

Yapıcı ve saygılı yorumlar bekliyoruz. Topluluk kuralları