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cs.CV2025
DiverseAR: Boosting Diversity in Bitwise Autoregressive Image Generation
Ying Yang, Zhengyao Lv, Tianlin Pan +5
In this paper, we investigate the underexplored challenge of sample diversity in autoregressive (AR) generative models with bitwise visual tokenizers. We first analyze the factors…
cs.CV2025
FlowSteer: Guiding Few-Step Image Synthesis with Authentic Trajectories
Lei Ke, Hubery Yin, Gongye Liu +6
With the success of flow matching in visual generation, sampling efficiency remains a critical bottleneck for its practical application. Among flow models' accelerating methods, Re…
cs.CV2025
Video Generation with Stable Transparency via Shiftable RGB-A Distribution Learner
Haotian Dong, Wenjing Wang, Chen Li +2
Generating RGB-A videos, which include alpha channels for transparency, has wide applications. However, current methods often suffer from low quality due to confusion between RGB a…