LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?

16 April 2024

Papers citing "LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?"

6 / 6 papers shown

Title
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets A. Blattmann Tim Dockhorn Sumith Kulal Daniel Mendelevitch Maciej Kilian ... Zion English Vikram S. Voleti Adam Letts Varun Jampani Robin Rombach VGen 150 985 0 25 Nov 2023
DiffusER: Discrete Diffusion via Edit-based Reconstruction Machel Reid Vincent J. Hellendoorn Graham Neubig DiffM 43 39 0 30 Oct 2022
CLIP-Diffusion-LM: Apply Diffusion Model on Image Captioning Shi-You Xu VLM DiffM 24 11 0 10 Oct 2022
Diffusion-LM Improves Controllable Text Generation Xiang Lisa Li John Thickstun Ishaan Gulrajani Percy Liang Tatsunori B. Hashimoto AI4CE 163 768 0 27 May 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015