25 citations · 62 across the 17 of their papers we have counts for
5 papers · 1 filter
ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis
Zanlin Ni, Yulin Wang, Renping Zhou +5
Recently, token-based generation have demonstrated their effectiveness in image synthesis. As a representative example, non-autoregressive Transformers (NATs) can generate decent-q…
AdaNAT: Exploring Adaptive Policy for Token-Based Image Generation
Zanlin Ni, Yulin Wang, Renping Zhou +6
Recent studies have demonstrated the effectiveness of token-based methods for visual content generation. As a representative work, non-autoregressive Transformers (NATs) are able t…
Revisiting Non-Autoregressive Transformers for Efficient Image Synthesis
Zanlin Ni, Yulin Wang, Renping Zhou +6
The field of image synthesis is currently flourishing due to the advancements in diffusion models. While diffusion models have been successful, their computational intensity has pr…
Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment
Jiayi Guo, Junhao Zhao, Chaoqun Du +6
Test-time adaptation (TTA) aims to improve the performance of source-domain pre-trained models on previously unseen, shifted target domains. Traditional TTA methods primarily adapt…
LLaVA-UHD: an LMM Perceiving Any Aspect Ratio and High-Resolution Images
Ruyi Xu, Yuan Yao, Zonghao Guo +7
Visual encoding constitutes the basis of large multimodal models (LMMs) in understanding the visual world. Conventional LMMs process images in fixed sizes and limited resolutions,…