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Found 13 papers, 3 papers with code
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Such a trade-off is referred to as the stabilityplasticity dilemma and is a more general and challenging problem for continual learning.
Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
Most existing methods for multi-source unsupervised domain adaptation (UDA) rely on a common encoder to extract domain-invariant features.
Multi-Source Unsupervised Domain Adaptation
Unsupervised Domain Adaptation
Facial Attribute Transformers for Precise and Robust Makeup Transfer
In this paper, we address the problem of makeup transfer, which aims at transplanting the makeup from the reference face to the source face while preserving the identity of the source.
The MSR-Video to Text Dataset with Clean Annotations
We cleaned the MSR-VTT annotations by removing these problems, then tested several typical video captioning models on the cleaned dataset.
Delving Deeper into the Decoder for Video Captioning
Video captioning is an advanced multi-modal task which aims to describe a video clip using a natural language sentence.
TextScanner: Reading Characters in Order for Robust Scene Text Recognition
Driven by deep learning and the large volume of data, scene text recognition has evolved rapidly in recent years.
Ranked #10 on
Scene Text Recognition
on ICDAR2015
A Semantics-Assisted Video Captioning Model Trained with Scheduled Sampling
Given the features of a video, recurrent neural networks can be used to automatically generate a caption for the video.
Double-Coupling Learning for Multi-Task Data Stream Classification
Data stream classification methods demonstrate promising performance on a single data stream by exploring the cohesion in the data stream.
Multi-View Fuzzy Clustering with The Alternative Learning between Shared Hidden Space and Partition
How to exploit the relation-ship between different views effectively using the characteristic of multi-view data has become a crucial challenge.
Locality Preserving Projections for Grassmann manifold
Learning on Grassmann manifold has become popular in many computer vision tasks, with the strong capability to extract discriminative information for imagesets and videos.
Partial Least Squares Regression on Riemannian Manifolds and Its Application in Classifications
Partial least squares regression (PLSR) has been a popular technique to explore the linear relationship between two datasets.
Fast Optimization Algorithm on Riemannian Manifolds and Its Application in Low-Rank Representation
The paper addresses the problem of optimizing a class of composite functions on Riemannian manifolds and a new first order optimization algorithm (FOA) with a fast convergence rate is proposed.
The Extended UCB Policies for Frequentist Multi-armed Bandit Problems
The multi-armed bandit (MAB) problem is a widely studied model in the field of reinforcement learning.
