315 citations · 367 across the 7 of their papers we have counts for
7 papers
Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation
Jie An, Songyang Zhang, Harry Yang +4
We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion m…
Make-A-Video: Text-to-Video Generation without Text-Video Data
Uriel Singer, Adam Polyak, Thomas Hayes +10
We propose Make-A-Video -- an approach for directly translating the tremendous recent progress in Text-to-Image (T2I) generation to Text-to-Video (T2V). Our intuition is simple: le…
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
Francesco Pinto, Harry Yang, Ser-Nam Lim +2
We show that the effectiveness of the well celebrated Mixup [Zhang et al., 2018] can be further improved if instead of using it as the sole learning objective, it is utilized as an…
MUGEN: A Playground for Video-Audio-Text Multimodal Understanding and GENeration
Thomas Hayes, Songyang Zhang, Xi Yin +6
Multimodal video-audio-text understanding and generation can benefit from datasets that are narrow but rich. The narrowness allows bite-sized challenges that the research community…
Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer
Songwei Ge, Thomas Hayes, Harry Yang +5
Videos are created to express emotion, exchange information, and share experiences. Video synthesis has intrigued researchers for a long time. Despite the rapid progress driven by…
Robustness and Generalization via Generative Adversarial Training
Omid Poursaeed, Tianxing Jiang, Harry Yang +2
While deep neural networks have achieved remarkable success in various computer vision tasks, they often fail to generalize to new domains and subtle variations of input images. Se…
Fine-grained Synthesis of Unrestricted Adversarial Examples
Omid Poursaeed, Tianxing Jiang, Yordanos Goshu +3
We propose a novel approach for generating unrestricted adversarial examples by manipulating fine-grained aspects of image generation. Unlike existing unrestricted attacks that typ…