373 citations · 539 across the 7 of their papers we have counts for
6 papers · 1 filter
Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models
Zijian Zhang, Zhou Zhao, Zhijie Lin
Diffusion Probabilistic Models (DPMs) have shown a powerful capacity of generating high-quality image samples. Recently, diffusion autoencoders (Diff-AE) have been proposed to expl…
Pseudo Numerical Methods for Diffusion Models on Manifolds
Luping Liu, Yi Ren, Zhijie Lin +1
Denoising Diffusion Probabilistic Models (DDPMs) can generate high-quality samples such as image and audio samples. However, DDPMs require hundreds to thousands of iterations to pr…
A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples
Sen Jia, Shuguo Jiang, Zhijie Lin +3
With the rapid development of deep learning technology and improvement in computing capability, deep learning has been widely used in the field of hyperspectral image (HSI) classif…
Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding
Zhu Zhang, Zhou Zhao, Zhijie Lin +2
Spatio-temporal video grounding aims to retrieve the spatio-temporal tube of a queried object according to the given sentence. Currently, most existing grounding methods are restri…
Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos
Zhu Zhang, Zhijie Lin, Zhou Zhao +2
Video moment retrieval aims to localize the target moment in an video according to the given sentence. The weak-supervised setting only provides the video-level sentence annotation…
Weakly-Supervised Video Moment Retrieval via Semantic Completion Network
Zhijie Lin, Zhou Zhao, Zhu Zhang +2
Video moment retrieval is to search the moment that is most relevant to the given natural language query. Existing methods are mostly trained in a fully-supervised setting, which r…