233 citations · 519 across the 15 of their papers we have counts for
4 papers · 1 filter
GenScale: A Benchmark for Relative Object Scale in Image Generation and Editing
Lingxiao Li, Max Whitton, Ledell Wu +1
Modern image generation and editing systems can produce photorealistic, prompt-aligned images, but still often render familiar objects at implausible relative sizes. To measure thi…
AltDiffusion: A Multilingual Text-to-Image Diffusion Model
Fulong Ye, Guang Liu, Xinya Wu +1
Large Text-to-Image(T2I) diffusion models have shown a remarkable capability to produce photorealistic and diverse images based on text inputs. However, existing works only support…
EVA-CLIP: Improved Training Techniques for CLIP at Scale
Quan Sun, Yuxin Fang, Ledell Wu +2
Contrastive language-image pre-training, CLIP for short, has gained increasing attention for its potential in various scenarios. In this paper, we propose EVA-CLIP, a series of mod…
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
Yuxin Fang, Wen Wang, Binhui Xie +6
We launch EVA, a vision-centric foundation model to explore the limits of visual representation at scale using only publicly accessible data. EVA is a vanilla ViT pre-trained to re…