Search Results for author:
Found 15 papers, 7 papers with code
DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments
In response to these challenges, this study introduces the novel task of 3D Reconstruction in Rainy Environments (3DRRE), specifically designed to address the complexities of reconstructing 3D scenes under rainy conditions.
LSD3K: A Benchmark for Smoke Removal from Laparoscopic Surgery Images
To advance this field, we construct a new high-quality dataset for Laparoscopic Surgery image Desmoking, named LSD3K, consisting of 3, 000 paired synthetic non-homogeneous smoke images.
Technique Report of CVPR 2024 PBDL Challenges
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies.
Dual-Path Multi-Scale Transformer for High-Quality Image Deraining
Despite the superiority of convolutional neural networks (CNNs) and Transformers in single-image rain removal, current multi-scale models still face significant challenges due to their reliance on single-scale feature pyramid patterns.
Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method
In this paper, we focus on the task of UHD image deraining, and contribute the first large-scale UHD image deraining dataset, 4K-Rain13k, that contains 13, 000 image pairs at 4K resolution.
RSDehamba: Lightweight Vision Mamba for Remote Sensing Satellite Image Dehazing
To this end, we propose the first lightweight network on the mamba-based model called RSDhamba in the field of RSID.
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
UAV-Rain1k: A Benchmark for Raindrop Removal from UAV Aerial Imagery
Raindrops adhering to the lens of UAVs can obstruct visibility of the background scene and degrade image quality.
Node-based Knowledge Graph Contrastive Learning for Medical Relationship Prediction
Particularly in biomedical relationship prediction tasks, NC-KGE outperforms all baselines on datasets such as PharmKG8k-28, DRKG17k-21, and BioKG72k-14, especially in predicting drug combination relationships.
Learning Image Deraining Transformer Network with Dynamic Dual Self-Attention
Recently, Transformer-based architecture has been introduced into single image deraining task due to its advantage in modeling non-local information.
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant Consistency
In this paper, an equivariant consistency model (EC-Conf) was proposed as a fast diffusion method for low-energy conformation generation.
Phenotypic Profiling of High Throughput Imaging Screens with Generic Deep Convolutional Features
While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure.
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Generative models are becoming a tool of choice for exploring the molecular space.
Application of generative autoencoder in de novo molecular design
A major challenge in computational chemistry is the generation of novel molecular structures with desirable pharmacological and physiochemical properties.
Molecular De Novo Design through Deep Reinforcement Learning
This work introduces a method to tune a sequence-based generative model for molecular de novo design that through augmented episodic likelihood can learn to generate structures with certain specified desirable properties.
