Search Results for author:
Found 18 papers, 4 papers with code
Zero-Shot Image Super-Resolution with Depth Guided Internal Degradation Learning
In the past few years, we have witnessed the great progress of image super-resolution (SR) thanks to the power of deep learning.
Constraint Learning for Parametric Point Cloud
Stage 1 extracts constraints from B-Rep data or point cloud.
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of users, assisting them with a wide range of tasks through conversational interfaces.
Training-Free Point Cloud Recognition Based on Geometric and Semantic Information Fusion
For the geometric branch, we adopt a non-parametric strategy to extract geometric features.
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
Advancements in autonomous driving have increasingly focused on end-to-end (E2E) systems that manage the full spectrum of driving tasks, from environmental perception to vehicle navigation and control.
MOT: A Mixture of Actors Reinforcement Learning Method by Optimal Transport for Algorithmic Trading
In this paper, we propose MOT, which designs multiple actors with disentangled representation learning to model the different patterns of the market.
Deep Reinforcement Learning for Real-Time Ground Delay Program Revision and Corresponding Flight Delay Assignments
This paper explores the optimization of Ground Delay Programs (GDP), a prevalent Traffic Management Initiative used in Air Traffic Management (ATM) to reconcile capacity and demand discrepancies at airports.
Airport Delay Prediction with Temporal Fusion Transformers
Since flight delay hurts passengers, airlines, and airports, its prediction becomes crucial for the decision-making of all stakeholders in the aviation industry and thus has been attempted by various previous research.
Corporate Credit Rating: A Survey
Corporate credit rating (CCR) plays a very important role in the process of contemporary economic and social development.
xASTNN: Improved Code Representations for Industrial Practice
The proposed xASTNN has three advantages.
Intelligent Painter: Picture Composition With Resampling Diffusion Model
Have you ever thought that you can be an intelligent painter?
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution
In our SF-SIM, we propose a noise estimator which can effectively suppress the noise in the image and enable our method to work under the low light and short exposure environment, without the need for stacking multiple frames for non-local denoising.
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
AIM 2019 Challenge on Image Demoireing: Methods and Results
A new dataset, called LCDMoire was created for this challenge, and consists of 10, 200 synthetically generated image pairs (moire and clean ground truth).
Multi-scale Dynamic Feature Encoding Network for Image Demoireing
The prevalence of digital sensors, such as digital cameras and mobile phones, simplifies the acquisition of photos.
Triple Attention Mixed Link Network for Single Image Super Resolution
Single image super resolution is of great importance as a low-level computer vision task.
Polynomial Regression As an Alternative to Neural Nets
Despite the success of neural networks (NNs), there is still a concern among many over their "black box" nature.
SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks
Single image super resolution is a very important computer vision task, with a wide range of applications.
Ranked #40 on
Image Super-Resolution
on BSD100 - 4x upscaling
