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Found 4 papers, 4 papers with code
Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation
We hypothesize that the latent representation learned from a pretrained generative T2V model encapsulates rich semantics and coherent temporal correspondences, thereby naturally facilitating video understanding.
Referring Video Object Segmentation
Semantic Segmentation
+2
Designing a Better Asymmetric VQGAN for StableDiffusion
The training cost of our asymmetric VQGAN is cheap, and we only need to retrain a new asymmetric decoder while keeping the vanilla VQGAN encoder and StableDiffusion unchanged.
Exploring Discrete Diffusion Models for Image Captioning
The image captioning task is typically realized by an auto-regressive method that decodes the text tokens one by one.
Enriching Local and Global Contexts for Temporal Action Localization
We explore two existing models to be the P-Net in our experiments.
