Merge branch 'main' of github.com:stephanie-fu/dreamsim

README.md

@@ -16,6 +16,12 @@ Current metrics for perceptual image similarity operate at the level of pixels a
 
 DreamSim is a new metric for perceptual image similarity that bridges the gap between "low-level" metrics (e.g. LPIPS, PSNR, SSIM) and "high-level" measures (e.g. CLIP). Our model was trained by concatenating CLIP, OpenCLIP, and DINO embeddings, and then finetuning on human perceptual judgements. We gathered these judgements on a dataset of ~20k image triplets, generated by diffusion models. Our model achieves better alignment with human similarity judgements than existing metrics, and can be used for downstream applications such as image retrieval.
 
+## 🕰️ Coming soon
+* JND Dataset release
+* Distilled DreamSim models (i.e. smaller models distilled from the main ensemble)
+* DreamSim variants trained for higher resolutions
+* Compatibility with the most recent version of PEFT
+
 ## 🚀 Updates
 
 **7/14/23:** Released three variants of DreamSim that each only use one finetuned ViT model instead of the full ensemble. These single-branch models provide a ~3x speedup over the full ensemble.