311 citations · 1k across the 56 of their papers we have counts for
64 papers · 1 filter
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou +1
Diffusion probabilistic models (DPMs) have shown remarkable performance in visual synthesis but are computationally expensive due to the need for multiple evaluations during the sa…
Token-Label Alignment for Vision Transformers
Han Xiao, Wenzhao Zheng, Zheng Zhu +2
Data mixing strategies (e.g., CutMix) have shown the ability to greatly improve the performance of convolutional neural networks (CNNs). They mix two images as inputs for training…
OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions
Chengkun Wang, Wenzhao Zheng, Zheng Zhu +2
The pretrain-finetune paradigm in modern computer vision facilitates the success of self-supervised learning, which tends to achieve better transferability than supervised learning…
Probabilistic Deep Metric Learning for Hyperspectral Image Classification
Chengkun Wang, Wenzhao Zheng, Xian Sun +2
This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image capt…
SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation
Ziyi Wang, Yongming Rao, Xumin Yu +2
Conventional point cloud semantic segmentation methods usually employ an encoder-decoder architecture, where mid-level features are locally aggregated to extract geometric informat…