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20172026
most citedLumiere: A Space-Time Diffusion Model for Video Generation

17 citations · 27 across the 13 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

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…

cs.CV2024

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…

cs.CV20243 cited

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…

cs.CV202417 cited

Lumiere: A Space-Time Diffusion Model for Video Generation

Omer Bar-Tal, Hila Chefer, Omer Tov +14

We introduce Lumiere -- a text-to-video diffusion model designed for synthesizing videos that portray realistic, diverse and coherent motion -- a pivotal challenge in video synthes…

cs.CV2024

Boundary Attention: Learning curves, corners, junctions and grouping

Mia Gaia Polansky, Charles Herrmann, Junhwa Hur +3

We present a lightweight network that infers grouping and boundaries, including curves, corners and junctions. It operates in a bottom-up fashion, analogous to classical methods fo…