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Found 61 papers, 20 papers with code
Interactive Gadolinium-Free MRI Synthesis: A Transformer with Localization Prompt Learning
Contrast-enhanced magnetic resonance imaging (CE-MRI) is crucial for tumor detection and diagnosis, but the use of gadolinium-based contrast agents (GBCAs) in clinical settings raises safety concerns due to potential health risks.
Seeing A 3D World in A Grain of Sand
We present a snapshot imaging technique for recovering 3D surrounding views of miniature scenes.
FocalCount: Towards Class-Count Imbalance in Class-Agnostic Counting
In class-agnostic object counting, the goal is to estimate the total number of object instances in an image without distinguishing between specific categories.
FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
LLMs have revolutionized NLP and demonstrated potential across diverse domains.
A New Adversarial Perspective for LiDAR-based 3D Object Detection
Autonomous vehicles (AVs) rely on LiDAR sensors for environmental perception and decision-making in driving scenarios.
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios
Our survey organizes the findings into three core components: Game Framework, Social Agent, and Evaluation Protocol.
DynamicAvatars: Accurate Dynamic Facial Avatars Reconstruction and Precise Editing with Diffusion Models
Generating and editing dynamic 3D head avatars are crucial tasks in virtual reality and film production.
SCIGS: 3D Gaussians Splatting from a Snapshot Compressive Image
The proposed SCIGS is the first to reconstruct a 3D explicit scene from a single compressed image, extending its application to dynamic 3D scenes.
ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models
During the entity expansion process, the LLM is guided to generate sentences by replicating the structures of a set of specific \textsl{feature sentences}, extracted from the task sentences by clustering.
Training with Differential Privacy: A Gradient-Preserving Noise Reduction Approach with Provable Security
Deep learning models have been extensively adopted in various regions due to their ability to represent hierarchical features, which highly rely on the training set and procedures.
Quaternion Nuclear Norm minus Frobenius Norm Minimization for color image reconstruction
Color image restoration methods typically represent images as vectors in Euclidean space or combinations of three monochrome channels.
Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather Conditions
To promote the navigational safety of vessels, many computational methods have been presented to perform visual quality enhancement under poor weather conditions.
BiGS: Bidirectional Gaussian Primitives for Relightable 3D Gaussian Splatting
We present Bidirectional Gaussian Primitives, an image-based novel view synthesis technique designed to represent and render 3D objects with surface and volumetric materials under dynamic illumination.
How to Best Combine Demosaicing and Denoising?
The real problem is to jointly denoise and demosaic noisy raw images.
Deep Inertia $L_p$ Half-Quadratic Splitting Unrolling Network for Sparse View CT Reconstruction
Sparse view computed tomography (CT) reconstruction poses a challenging ill-posed inverse problem, necessitating effective regularization techniques.
Zero-shot Object Counting with Good Exemplars
Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations.
OneRestore: A Universal Restoration Framework for Composite Degradation
In real-world scenarios, image impairments often manifest as composite degradations, presenting a complex interplay of elements such as low light, haze, rain, and snow.
Ranked #1 on
Rain Removal
on DID-MDN
HSIDMamba: Exploring Bidirectional State-Space Models for Hyperspectral Denoising
Effectively discerning spatial-spectral dependencies in HSI denoising is crucial, but prevailing methods using convolution or transformers still face computational efficiency limitations.
Fast, nonlocal and neural: a lightweight high quality solution to image denoising
In this letter, we propose a solution to both issues by combining a nonlocal algorithm with a lightweight residual CNN.
Kernel Correlation-Dissimilarity for Multiple Kernel k-Means Clustering
The main objective of the Multiple Kernel k-Means (MKKM) algorithm is to extract non-linear information and achieve optimal clustering by optimizing base kernel matrices.
AoSRNet: All-in-One Scene Recovery Networks via Multi-knowledge Integration
Additionally, we suggest a multi-receptive field extraction module (MEM) to attenuate the loss of image texture details caused by GC nonlinear and OLS linear transformations.
Dual-Tap Optical-Digital Feedforward Equalization Enabling High-Speed Optical Transmission in IM/DD Systems
Intensity-modulation and direct-detection (IM/DD) transmission is widely adopted for high-speed optical transmission scenarios due to its cost-effectiveness and simplicity.
MvKSR: Multi-view Knowledge-guided Scene Recovery for Hazy and Rainy Degradation
High-quality imaging is crucial for ensuring safety supervision and intelligent deployment in fields like transportation and industry.
VectorTalker: SVG Talking Face Generation with Progressive Vectorisation
To address these, we propose a novel scalable vector graphic reconstruction and animation method, dubbed VectorTalker.
iComMa: Inverting 3D Gaussian Splatting for Camera Pose Estimation via Comparing and Matching
We present a method named iComMa to address the 6D camera pose estimation problem in computer vision.
A Region of Interest Focused Triple UNet Architecture for Skin Lesion Segmentation
Skin lesion segmentation is of great significance for skin lesion analysis and subsequent treatment.
Multi-Task Learning-Enabled Automatic Vessel Draft Reading for Intelligent Maritime Surveillance
The accurate and efficient vessel draft reading (VDR) is an important component of intelligent maritime surveillance, which could be exploited to assist in judging whether the vessel is normally loaded or overloaded.
Textureless Deformable Surface Reconstruction with Invisible Markers
Leveraging the markers, we design a multi-camera system that captures surface deformation under the UV light and the visible light in a time multiplexing fashion.
Synthesizing PET images from High-field and Ultra-high-field MR images Using Joint Diffusion Attention Model
JPD of MRI and noise-added PET was learned in the diffusion process.
DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation
To eliminate the influences of adverse weather conditions, we propose a dual attention and dual frequency-guided dehazing network (termed DADFNet) for real-time visibility enhancement.
SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing
The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details.
Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways
To further improve vessel traffic surveillance, it becomes necessary to fuse the AIS and video data to simultaneously capture the visual features, identity and dynamic information for the vessels of interest.
ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling
We address the problem by introducing a novel joint method on top of BERT which explicitly models the multiple sub-tokens features after wordpiece tokenization, thereby contributing to the two tasks.
SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.
Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields
Neural Radiance Fields (NeRF) have achieved photorealistic novel views synthesis; however, the requirement of accurate camera poses limits its application.
Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization
We develop two simple yet effective plug and play methods to improve the performance of existing local and non-local propagation-based VSR algorithms on widely-used public videos.
Action Recognition With Motion Diversification and Dynamic Selection
To address this issue, we introduce a Motion Diversification and Selection (MoDS) module to generate diversified spatio-temporal motion features and then select the suitable motion representation dynamically for categorizing the input video.
Ranked #19 on
Action Recognition
on Something-Something V1
MatchNorm: Learning-based Point Cloud Registration for 6D Object Pose Estimation in the Real World
Our two contributions are general and can be applied to many existing learning-based 3D object registration frameworks, which we illustrate by implementing them in two of them, DCP and IDAM.
UV Volumes for Real-time Rendering of Editable Free-view Human Performance
Neural volume rendering enables photo-realistic renderings of a human performer in free-view, a critical task in immersive VR/AR applications.
Deep Understanding based Multi-Document Machine Reading Comprehension
Most existing multi-document machine reading comprehension models mainly focus on understanding the interactions between the input question and documents, but ignore following two kinds of understandings.
Combining Intra-Risk and Contagion Risk for Enterprise Bankruptcy Prediction Using Graph Neural Networks
This study for the first time considers both types of risk and their joint effects in bankruptcy prediction.
Contrastive Vision-Language Pre-training with Limited Resources
However, these works require a tremendous amount of data and computational resources (e. g., billion-level web data and hundreds of GPUs), which prevent researchers with limited resources from reproduction and further exploration.
Doing Natural Language Processing in A Natural Way: An NLP toolkit based on object-oriented knowledge base and multi-level grammar base
We introduce an NLP toolkit based on object-oriented knowledge base and multi-level grammar base.
Stereo CenterNet based 3D Object Detection for Autonomous Driving
In this study, we propose a 3D object detection method, Stereo CenterNet (SC), using geometric information in stereo imagery.
A Method to Generate High Precision Mesh Model and RGB-D Datasetfor 6D Pose Estimation Task
Recently, 3D version has been improved greatly due to the development of deep neural networks.
MaterialGAN: Reflectance Capture using a Generative SVBRDF Model
We address the problem of reconstructing spatially-varying BRDFs from a small set of image measurements.
Pchatbot: A Large-Scale Dataset for Personalized Chatbot
This enables the development of personalized dialogue models that directly learn implicit user personality from the user's dialogue history.
Joint Demosaicking and Denoising Benefits from a Two-stage Training Strategy
Image demosaicking and denoising are the first two key steps of the color image production pipeline.
Low-Light Maritime Image Enhancement with Regularized Illumination Optimization and Deep Noise Suppression
To suppress the effect of unwanted noise on imaging performance, a deep learning-based blind denoising framework is further introduced to promote the visual quality of enhanced image.
LMVE at SemEval-2020 Task 4: Commonsense Validation and Explanation using Pretraining Language Model
This paper describes our submission to subtask a and b of SemEval-2020 Task 4.
Cross-dataset Training for Class Increasing Object Detection
Given two or more already labeled datasets that target for different object classes, cross-dataset training aims to detect the union of the different classes, so that we do not have to label all the classes for all the datasets.
A Bayesian Inference Framework for Procedural Material Parameter Estimation
Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability.
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).
Device-independent verification of Einstein-Podolsky-Rosen steering
We first establish the DI verification framework, relying on the measurement-device-independent technique and self-testing, and show it is able to verify all EPR-steerable states.
Quantum Physics
AdaCompress: Adaptive Compression for Online Computer Vision Services
Then we train the agent in a reinforcement learning way to adapt it for different deep learning cloud services that act as the {\em interactive training environment} and feeding a reward with comprehensive consideration of accuracy and data size.
Multimedia Image and Video Processing
STAC: Science Toolkit Based on Chinese Idiom Knowledge Graph
Chinese idioms (Cheng Yu) have seen five thousand years{'} history and culture of China, meanwhile they contain large number of scientific achievement of ancient China.
MSFD:Multi-Scale Receptive Field Face Detector
We simultaneously propose an anchor assignment strategy which can cover faces with a wide range of scales to improve the recall rate of small faces and rotated faces.
TechKG: A Large-Scale Chinese Technology-Oriented Knowledge Graph
In this work, we introduce TechKG, a large scale Chinese knowledge graph that is technology-oriented.
Enabling Automatic Certification of Online Auctions
This requires agents to have a deeper understanding of auction mechanisms and be able to verify desirable properties of a given mechanism.
