349 citations · 1.4k across the 30 of their papers we have counts for
8 papers · 1 filter
Diffusion Probabilistic Model Made Slim
Xingyi Yang, Daquan Zhou, Jiashi Feng +1
Despite the recent visually-pleasing results achieved, the massive computational cost has been a long-standing flaw for diffusion probabilistic models (DPMs), which, in turn, great…
Expanding Small-Scale Datasets with Guided Imagination
Yifan Zhang, Daquan Zhou, Bryan Hooi +2
The power of DNNs relies heavily on the quantity and quality of training data. However, collecting and annotating data on a large scale is often expensive and time-consuming. To ad…
MagicVideo: Efficient Video Generation With Latent Diffusion Models
Daquan Zhou, Weimin Wang, Hanshu Yan +3
We present an efficient text-to-video generation framework based on latent diffusion models, termed MagicVideo. MagicVideo can generate smooth video clips that are concordant with…
MagicMix: Semantic Mixing with Diffusion Models
Jun Hao Liew, Hanshu Yan, Daquan Zhou +1
Have you ever imagined what a corgi-alike coffee machine or a tiger-alike rabbit would look like? In this work, we attempt to answer these questions by exploring a new task called…
Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning
Dongze Lian, Daquan Zhou, Jiashi Feng +1
Existing fine-tuning methods either tune all parameters of the pre-trained model (full fine-tuning), which is not efficient, or only tune the last linear layer (linear probing), wh…
Sharpness-Aware Training for Free
Jiawei Du, Daquan Zhou, Jiashi Feng +2
Modern deep neural networks (DNNs) have achieved state-of-the-art performances but are typically over-parameterized. The over-parameterization may result in undesirably large gener…
MBEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation
Enze Xie, Zhiding Yu, Daquan Zhou +5
In this paper, we propose MBEV, a unified framework that jointly performs 3D object detection and map segmentation in the Birds Eye View~(BEV) space with multi-camera image inp…
Understanding The Robustness in Vision Transformers
Daquan Zhou, Zhiding Yu, Enze Xie +4
Recent studies show that Vision Transformers(ViTs) exhibit strong robustness against various corruptions. Although this property is partly attributed to the self-attention mechanis…