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Found 5 papers, 4 papers with code
Large Language Models are Frame-level Directors for Zero-shot Text-to-Video Generation
In the paradigm of AI-generated content (AIGC), there has been increasing attention in extending pre-trained text-to-image (T2I) models to text-to-video (T2V) generation.
Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation
In this work, we explore existing frameworks for score-distilling text-to-3D generation and identify the main causes of the view inconsistency problem -- the embedded bias of 2D diffusion models.
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
Generative models have recently undergone significant advancement due to the diffusion models.
Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence
Existing pipelines of semantic correspondence commonly include extracting high-level semantic features for the invariance against intra-class variations and background clutters.
Improving Sample Quality of Diffusion Models Using Self-Attention Guidance
Denoising diffusion models (DDMs) have attracted attention for their exceptional generation quality and diversity.
