Archived
2026-08-31Video Generative Models as Geometry Learner
Haosen Yang, Jifei Song, Zhensong Zhang, Xiatian Zhu, Jiankang Deng
arXiv:2608.28549v1Today’s pick is a clever way to turn video generation models into geometry solvers. The problem is that estimating depth and surface normals from a single image usually needs lots of labeled data, and many recent generative methods either train separate models for each geometry task or fine-tune large diffusion backbones with expensive supervision. This paper, GeoNeXt, takes a different route: it repurposes a pretrained video generative model and frames geometry prediction as next-frame forecasting. That lets the model use the temporal structure it already understands as a strong prior, while jointly learning image-to-geometry and geometry-to-image relationships. The result is a more data-efficient system that can produce both depth and surface normals, even in zero-shot settings. What makes this interesting is the broader idea: instead of building a new model from scratch for every vision task, we can sometimes unlock powerful representations by changing how we ask the model to predict. That matters for robotics, AR, 3D reconstruction, and any application where geometry is needed but labels are scarce.
Also spotted that day
QGPINNs: A Physics-Informed Neural Network Framework for Nonlocal Differential Equations on Quantum GraphsAero Hand Open: A Simulation-Ready Tendon-Driven Hand for Dexterous Manipulation LearningLearning a Size-Weight Frontier for Synthetic-Augmented InferenceOn two proofs of $d^2$ mixing of weighted Dikin walksLearning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropyA Formal Limitation on Learning Human Language From Textual CorporaBlog: Survey of OptimizersLogos: An Agent Harness on a Cross-Process BusAdvancing Interaction-Sensitive Feature Selection: Novel Relief-Based Algorithms, Expanded Comparisons, and Recommendations for Biomedical Data MiningDARTS: Decoder-Aware Representation Tuning via Surgery for Model MergingAn Enclosed Mode Is a Gauge Choice: Topology Relative to Reach in Certified Code World ModelsInstructMesh: Selective Refinement of Generative 3D Models for FabricationTexture Image Classification Using DWT AlexNet Feature Fusion and Deep Neural NetworksWhen Robots Mishear Us: Mapping the Safety Risks of Voice-Controlled Embodied AI
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