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Found 3 papers, 1 papers with code
Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the Wild
In this study, we explore a universal model that can flexibly adapt to unseen dense label structures with a few examples, enabling it to serve as a data-efficient vision generalist in diverse real-world scenarios.
Utilizing Neural Transducers for Two-Stage Text-to-Speech via Semantic Token Prediction
We also delve into the inference speed and prosody control capabilities of our approach, highlighting the potential of neural transducers in TTS frameworks.
Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers
However, the transformers are prohibited from directly learning the long-term dependency in videos due to the quadratic complexity of self-attention, and inherently suffering from slow inference time and error propagation due to the autoregressive process.
Ranked #24 on
Video Generation
on UCF-101
