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20242026
most citedSF-V: Single Forward Video Generation Model

1 citations · 2 across the 17 of their papers we have counts for

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9 papers · 1 filter

cs.CV2024

SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training

Dongting Hu, Jierun Chen, Xijie Huang +16

Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to…

cs.CV2024

SnapGen-V: Generating a Five-Second Video within Five Seconds on a Mobile Device

Yushu Wu, Zhixing Zhang, Yanyu Li +11

We have witnessed the unprecedented success of diffusion-based video generation over the past year. Recently proposed models from the community have wielded the power to generate c…

cs.CV2024

AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation

Anil Kag, Huseyin Coskun, Jierun Chen +5

Neural network architecture design requires making many crucial decisions. The common desiderata is that similar decisions, with little modifications, can be reused in a variety of…

cs.CV2024

Scalable Ranked Preference Optimization for Text-to-Image Generation

Shyamgopal Karthik, Huseyin Coskun, Zeynep Akata +3

Direct Preference Optimization (DPO) has emerged as a powerful approach to align text-to-image (T2I) models with human feedback. Unfortunately, successful application of DPO to T2I…

cs.GR2024

Lightweight Predictive 3D Gaussian Splats

Junli Cao, Vidit Goel, Chaoyang Wang +6

Recent approaches representing 3D objects and scenes using Gaussian splats show increased rendering speed across a variety of platforms and devices. While rendering such representa…

cs.CV2024★ 1 cited

BitsFusion: 1.99 bits Weight Quantization of Diffusion Model

Yang Sui, Yanyu Li, Anil Kag +7

Diffusion-based image generation models have achieved great success in recent years by showing the capability of synthesizing high-quality content. However, these models contain a…

cs.CV2024★ 1 cited

SF-V: Single Forward Video Generation Model

Zhixing Zhang, Yanyu Li, Yushu Wu +9

Diffusion-based video generation models have demonstrated remarkable success in obtaining high-fidelity videos through the iterative denoising process. However, these models requir…

cs.CV2024

TextCraftor: Your Text Encoder Can be Image Quality Controller

Yanyu Li, Xian Liu, Anil Kag +6

Diffusion-based text-to-image generative models, e.g., Stable Diffusion, have revolutionized the field of content generation, enabling significant advancements in areas like image…

cs.CV2024

Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis

Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov +8

Contemporary models for generating images show remarkable quality and versatility. Swayed by these advantages, the research community repurposes them to generate videos. Since vide…