Search Results for author:
Found 22 papers, 9 papers with code
Learning-at-Criticality in Large Language Models for Quantum Field Theory and Beyond
Fundamental physics often confronts complex symbolic problems with few guiding exemplars or established principles.
UrbanCraft: Urban View Extrapolation via Hierarchical Sem-Geometric Priors
Existing neural rendering-based urban scene reconstruction methods mainly focus on the Interpolated View Synthesis (IVS) setting that synthesizes from views close to training camera trajectory.
A New Segment Routing method with Swap Node Selection Strategy Based on Deep Reinforcement Learning for Software Defined Network
The existing segment routing (SR) methods need to determine the routing first and then use path segmentation approaches to select swap nodes to form a segment routing path (SRP).
Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework
To address these challenges, we introduce a comprehensive geolocation framework with three key components: GeoComp, a large-scale dataset; GeoCoT, a novel reasoning method; and GeoEval, an evaluation metric, collectively designed to address critical challenges and drive advancements in geolocation research.
Range and Bird's Eye View Fused Cross-Modal Visual Place Recognition
Compared to single-modal VPR, this approach benefits from the widespread availability of RGB cameras and the robustness of point clouds in providing accurate spatial geometry and distance information.
Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement
However, existing methods rely heavily on annotated data, and struggle with effectively disentangling timbre and style, leading to challenges in achieving controllable generation, especially in zero-shot scenarios.
Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis
Artificial intelligence (AI) methodologies hold great promise for the rapid and accurate diagnosis of coronary artery disease (CAD) from intravascular optical coherent tomography (IVOCT) images.
GSGTrack: Gaussian Splatting-Guided Object Pose Tracking from RGB Videos
Tracking the 6DoF pose of unknown objects in monocular RGB video sequences is crucial for robotic manipulation.
Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation
In this paper, we propose a new approach to perform supervised texture classification/segmentation.
Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets
Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterize different textures.
MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
MMAC-Copilot: Multi-modal Agent Collaboration Operating Copilot
To address this, we propose the Multi-Modal Agent Collaboration framework (MMAC-Copilot), a framework utilizes the collective expertise of diverse agents to enhance interaction ability with application.
Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs.
NTIRE 2024 Challenge on Image Super-Resolution ($\times$4): Methods and Results
This paper reviews the NTIRE 2024 challenge on image super-resolution ($\times$4), highlighting the solutions proposed and the outcomes obtained.
End-to-end Rain Streak Removal with RAW Images
To be specific, we generate rainy RAW data by converting color rain streak into RAW space and design simple but efficient RAW processing algorithms to synthesize both rainy and clean color images.
Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions?
Data augmentation via back-translation is common when pretraining Vision-and-Language Navigation (VLN) models, even though the generated instructions are noisy.
TextSLAM: Visual SLAM with Semantic Planar Text Features
The results show that integrating texture features leads to a more superior SLAM system that can match images across day and night.
Exploring Representation-Level Augmentation for Code Search
In this paper, we explore augmentation methods that augment data (both code and query) at representation level which does not require additional data processing and training, and based on this we propose a general format of representation-level augmentation that unifies existing methods.
StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation
Inspired by the early works on indoor modeling, we leverage the structural regularities exhibited in indoor scenes, to train a better depth network.
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
The current state-of-the-art approaches for medical image classification rely on using the de-facto method for ConvNets - fine-tuning.
Cancer-no cancer per image classification
image-classification
+4
Air Quality Prediction Using Improved PSO-BP Neural Network
Predicting urban air quality is a significant aspect of preventing urban air pollution and improving the living environment of urban residents.
Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image
A simple but useful observation on our NAC is: as long as the noise is weak, it is feasible to learn a self-supervised network only with the corrupted image, approximating the optimal parameters of a supervised network learned with pairs of noisy and clean images.
