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Found 4 papers, 4 papers with code
ModelScope Text-to-Video Technical Report
This paper introduces ModelScopeT2V, a text-to-video synthesis model that evolves from a text-to-image synthesis model (i. e., Stable Diffusion).
Ranked #4 on
Text-to-Video Generation
on MSR-VTT
VideoComposer: Compositional Video Synthesis with Motion Controllability
The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis.
Ranked #5 on
Text-to-Video Generation
on MSR-VTT
VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation
A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate new samples, has been shown to handle complex data distribution.
Ranked #2 on
Text-to-Video Generation
on UCF-101
Multi-Task Recommendations with Reinforcement Learning
To be specific, the RMTL structure can address the two aforementioned issues by (i) constructing an MTL environment from session-wise interactions and (ii) training multi-task actor-critic network structure, which is compatible with most existing MTL-based recommendation models, and (iii) optimizing and fine-tuning the MTL loss function using the weights generated by critic networks.
