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20232026
most citedModelScope Text-to-Video Technical Report

47 citations · 106 across the 24 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

cs.CV2023★ 2 cited

A Recipe for Scaling up Text-to-Video Generation with Text-free Videos

Xiang Wang, Shiwei Zhang, Hangjie Yuan +6

Diffusion-based text-to-video generation has witnessed impressive progress in the past year yet still falls behind text-to-image generation. One of the key reasons is the limited s…

cs.CV2023★ 1 cited

InstructVideo: Instructing Video Diffusion Models with Human Feedback

Hangjie Yuan, Shiwei Zhang, Xiang Wang +7

Diffusion models have emerged as the de facto paradigm for video generation. However, their reliance on web-scale data of varied quality often yields results that are visually unap…

cs.CV2023★ 1 cited

Hierarchical Spatio-temporal Decoupling for Text-to-Video Generation

Zhiwu Qing, Shiwei Zhang, Jiayu Wang +5

Despite diffusion models having shown powerful abilities to generate photorealistic images, generating videos that are realistic and diverse still remains in its infancy. One of th…

cs.CV2023★ 6 cited

DreamVideo: Composing Your Dream Videos with Customized Subject and Motion

Yujie Wei, Shiwei Zhang, Zhiwu Qing +6

Customized generation using diffusion models has made impressive progress in image generation, but remains unsatisfactory in the challenging video generation task, as it requires t…

cs.CV2023★ 9 cited

DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models

Yifeng Ma, Shiwei Zhang, Jiayu Wang +3

Emotional talking head generation has attracted growing attention. Previous methods, which are mainly GAN-based, still struggle to consistently produce satisfactory results across…

cs.CV2023★ 22 cited

I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models

Shiwei Zhang, Jiayu Wang, Yingya Zhang +6

Video synthesis has recently made remarkable strides benefiting from the rapid development of diffusion models. However, it still encounters challenges in terms of semantic accurac…

cs.CV2023

Few-shot Action Recognition with Captioning Foundation Models

Xiang Wang, Shiwei Zhang, Hangjie Yuan +4

Transferring vision-language knowledge from pretrained multimodal foundation models to various downstream tasks is a promising direction. However, most current few-shot action reco…

cs.CV2023★ 2 cited

RLIPv2: Fast Scaling of Relational Language-Image Pre-training

Hangjie Yuan, Shiwei Zhang, Xiang Wang +7

Relational Language-Image Pre-training (RLIP) aims to align vision representations with relational texts, thereby advancing the capability of relational reasoning in computer visio…

cs.CV2023★ 47 cited

ModelScope Text-to-Video Technical Report

Jiuniu Wang, Hangjie Yuan, Dayou Chen +3

This paper introduces ModelScopeT2V, a text-to-video synthesis model that evolves from a text-to-image synthesis model (i.e., Stable Diffusion). ModelScopeT2V incorporates spatio-t…

cs.CV2023

CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic Segmentation

Jun Cen, Shiwei Zhang, Yixuan Pei +5

2D RGB images and 3D LIDAR point clouds provide complementary knowledge for the perception system of autonomous vehicles. Several 2D and 3D fusion methods have been explored for th…