540 citations · 651 across the 21 of their papers we have counts for
4 papers · 2 filters
Language-only Efficient Training of Zero-shot Composed Image Retrieval
Geonmo Gu, Sanghyuk Chun, Wonjae Kim +2
Composed image retrieval (CIR) task takes a composed query of image and text, aiming to search relative images for both conditions. Conventional CIR approaches need a training data…
What Do Self-Supervised Vision Transformers Learn?
Namuk Park, Wonjae Kim, Byeongho Heo +2
We present a comparative study on how and why contrastive learning (CL) and masked image modeling (MIM) differ in their representations and in their performance of downstream tasks…
CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
Geonmo Gu, Sanghyuk Chun, Wonjae Kim +3
This paper proposes a novel diffusion-based model, CompoDiff, for solving zero-shot Composed Image Retrieval (ZS-CIR) with latent diffusion. This paper also introduces a new synthe…
SeiT: Storage-Efficient Vision Training with Tokens Using 1% of Pixel Storage
Song Park, Sanghyuk Chun, Byeongho Heo +2
We need billion-scale images to achieve more generalizable and ground-breaking vision models, as well as massive dataset storage to ship the images (e.g., the LAION-4B dataset need…