most citedMicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation

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cs.CV2024

Event-boosted Deformable 3D Gaussians for Dynamic Scene Reconstruction

Wenhao Xu, Wenming Weng, Yueyi Zhang +2

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the…

cs.CV2024

CEIA: CLIP-Based Event-Image Alignment for Open-World Event-Based Understanding

Wenhao Xu, Wenming Weng, Yueyi Zhang +1

We present CEIA, an effective framework for open-world event-based understanding. Currently training a large event-text model still poses a huge challenge due to the shortage of pa…

cs.CV2024

Event-assisted Low-Light Video Object Segmentation

Hebei Li, Jin Wang, Jiahui Yuan +6

In the realm of video object segmentation (VOS), the challenge of operating under low-light conditions persists, resulting in notably degraded image quality and compromised accurac…

cs.CV20231 cited

MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation

Yanhui Wang, Jianmin Bao, Wenming Weng +12

We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation. Unlike existing approaches that align text prompts with vi…

cs.CV2023

ARTV: Auto-Regressive Text-to-Video Generation with Diffusion Models

Wenming Weng, Ruoyu Feng, Yanhui Wang +10

We present ARTV, an efficient framework for auto-regressive video generation with diffusion models. Unlike existing methods that generate entire videos in one-s…

cs.CV2023

EGVD: Event-Guided Video Deraining

Yueyi Zhang, Jin Wang, Wenming Weng +2

With the rapid development of deep learning, video deraining has experienced significant progress. However, existing video deraining pipelines cannot achieve satisfying performance…