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20242026
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cs.CV2026

AdaGen: Learning Adaptive Policy for Image Synthesis

Zanlin Ni, Yulin Wang, Yeguo Hua +5

Recent advances in image synthesis have been propelled by powerful generative models, such as Masked Generative Transformers (MaskGIT), autoregressive models, diffusion models, and…

cs.CV2025

4D LangSplat: 4D Language Gaussian Splatting via Multimodal Large Language Models

Wanhua Li, Renping Zhou, Jiawei Zhou +5

Learning 4D language fields to enable time-sensitive, open-ended language queries in dynamic scenes is essential for many real-world applications. While LangSplat successfully grou…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…