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cs.CV2026
Kimodo: Scaling Controllable Human Motion Generation
Davis Rempe, Mathis Petrovich, Ye Yuan +21
High-quality human motion data is becoming increasingly important for applications in robotics, simulation, and entertainment. Recent generative models offer a potential data sourc…
cs.CV2021★ 1 cited
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting
Zian Wang, Jonah Philion, Sanja Fidler +1
In this work, we address the problem of jointly estimating albedo, normals, depth and 3D spatially-varying lighting from a single image. Most existing methods formulate the task as…