From the 1 of 6 linked papers with an AI index.
6 papers
GeCo: Evaluating Geometric Consistency for Video Generation via Motion and Structure
Leslie Gu, Junhwa Hur, Charles Herrmann +4
GeCo is a geometry-based metric that detects deformation and occlusion inconsistencies in generated videos by combining residual motion and depth cues, providing dense consistency…
GR3EN: Generative Relighting for 3D Environments
Xiaoyan Xing, Philipp Henzler, Junhwa Hur +4
We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-con…
MASIV: Toward Material-Agnostic System Identification from Videos
Yizhou Zhao, Haoyu Chen, Chunjiang Liu +7
System identification from videos aims to recover object geometry and governing physical laws. Existing methods integrate differentiable rendering with simulation but rely on prede…
MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion
Junyi Zhang, Charles Herrmann, Junhwa Hur +5
Estimating geometry from dynamic scenes, where objects move and deform over time, remains a core challenge in computer vision. Current approaches often rely on multi-stage pipeline…
High-Resolution Frame Interpolation with Patch-based Cascaded Diffusion
Junhwa Hur, Charles Herrmann, Saurabh Saxena +6
Despite the recent progress, existing frame interpolation methods still struggle with processing extremely high resolution input and handling challenging cases such as repetitive t…
Motion Prompting: Controlling Video Generation with Motion Trajectories
Daniel Geng, Charles Herrmann, Junhwa Hur +11
Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text prompts for control, which stru…