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Found 18 papers, 8 papers with code
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Integral to RPI are Robust Active Policy Selection (RAPS) and Robust Policy Gradient (RPG), both of which reason over whether to perform state-wise imitation from the oracles or learn from its own value function when the learner's performance surpasses that of the oracles in a specific state.
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration
The reasoning behind this approach is understandable, as localizing parameters that are easily influenced by non-IID data can prevent the potential negative effect of collaboration.
Take Your Pick: Enabling Effective Personalized Federated Learning within Low-dimensional Feature Space
FedPick achieves PFL in the low-dimensional feature space by selecting task-relevant features adaptively for each client from the features generated by the global encoder based on its local data distribution.
3Deformer: A Common Framework for Image-Guided Mesh Deformation
Unlike these studies, our 3Deformer is a non-training and common framework, which only requires supervision of readily-available semantic images, and is compatible with editing various objects unlimited by datasets.
Active Policy Improvement from Multiple Black-box Oracles
We introduce MAPS and MAPS-SE, a class of policy improvement algorithms that perform imitation learning from multiple suboptimal oracles.
Unlocking the Potential of Federated Learning for Deeper Models
Our further investigation shows that the decline is due to the continuous accumulation of dissimilarities among client models during the layer-by-layer back-propagation process, which we refer to as "divergence accumulation."
OpenVIS: Open-vocabulary Video Instance Segmentation
Open-vocabulary Video Instance Segmentation (OpenVIS) can simultaneously detect, segment, and track arbitrary object categories in a video, without being constrained to categories seen during training.
Cost-Effective Online Contextual Model Selection
In particular, we focus on the task of selecting pre-trained classifiers, and propose a contextual active model selection algorithm (CAMS), which relies on a novel uncertainty sampling query criterion defined on a given policy class for adaptive model selection.
SentiStory: A Multi-Layered Sentiment-Aware Generative Model for Visual Storytelling
The visual storytelling (VIST) task aims at generating reasonable, human-like and coherent stories with the image streams as input.
Ranked #5 on
Visual Storytelling
on VIST
MARVEL: Raster Manga Vectorization via Primitive-wise Deep Reinforcement Learning
Manga is a fashionable Japanese-style comic form that is composed of black-and-white strokes and is generally displayed as raster images on digital devices.
ArtCoder: An End-to-End Method for Generating Scanning-Robust Stylized QR Codes
Quick Response (QR) code is one of the most worldwide used two-dimensional codes.
Visformer: The Vision-friendly Transformer
The past year has witnessed the rapid development of applying the Transformer module to vision problems.
Ranked #507 on
Image Classification
on ImageNet
SelectScale: Mining More Patterns from Images via Selective and Soft Dropout
Instead of randomly dropping units, SelectScale selects the important features in networks and adjusts them during training.
An End-to-end Method for Producing Scanning-robust Stylized QR Codes
Quick Response (QR) code is one of the most worldwide used two-dimensional codes.~Traditional QR codes appear as random collections of black-and-white modules that lack visual semantics and aesthetic elements, which inspires the recent works to beautify the appearances of QR codes.
Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
A Survey on Incorporating Domain Knowledge into Deep Learning for Medical Image Analysis
Although deep learning models like CNNs have achieved great success in medical image analysis, the small size of medical datasets remains a major bottleneck in this area.
MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing
Manga is a world popular comic form originated in Japan, which typically employs black-and-white stroke lines and geometric exaggeration to describe humans' appearances, poses, and actions.
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio
Automatic designing computationally efficient neural networks has received much attention in recent years.
