2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2023
AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration
Lijiang Li, Huixia Li, Xiawu Zheng +7
Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such t…
cs.CV2023
UGC: Unified GAN Compression for Efficient Image-to-Image Translation
Yuxi Ren, Jie Wu, Peng Zhang +6
Recent years have witnessed the prevailing progress of Generative Adversarial Networks (GANs) in image-to-image translation. However, the success of these GAN models hinges on pond…
cs.CV2023★ 2 cited
AlignDet: Aligning Pre-training and Fine-tuning in Object Detection
Ming Li, Jie Wu, Xionghui Wang +6
The paradigm of large-scale pre-training followed by downstream fine-tuning has been widely employed in various object detection algorithms. In this paper, we reveal discrepancies…