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Found 29 papers, 8 papers with code
Neural Shrödinger Bridge Matching for Pansharpening
In this paper, we identify shortcomings in directly applying DPMs to the task of pansharpening as an inverse problem: 1) initiating sampling directly from Gaussian noise neglects the low-resolution multispectral image (LRMS) as a prior; 2) low sampling efficiency often necessitates a higher number of sampling steps.
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
Pansharpening is a significant image fusion technique that merges the spatial content and spectral characteristics of remote sensing images to generate high-resolution multispectral images.
A Novel State Space Model with Local Enhancement and State Sharing for Image Fusion
However, due to the nature of images different from casual language sequences, the limited state capacity of Mamba weakens its ability to model image information.
Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening
In this paper, we introduce a so-called content-adaptive non-local convolution (CANConv), a novel method tailored for remote sensing image pansharpening.
CMT: Cross Modulation Transformer with Hybrid Loss for Pansharpening
In response, we present the Cross Modulation Transformer (CMT), a pioneering method that modifies the attention mechanism.
DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception
The advancement of autonomous driving systems hinges on the ability to achieve low-latency and high-accuracy perception.
An FPGA-Based Accelerator Enabling Efficient Support for CNNs with Arbitrary Kernel Sizes
Particularly, it demonstrates efficient support for large-kernel CNNs, achieving throughputs of 169. 68 GOPS and 244. 55 GOPS for RepLKNet-31 and PyConvResNet-50, respectively, both of which are implemented on hardware for the first time.
Meta Reinforcement Learning for Multi-Task Offloading in Vehicular Edge Computing
The objective is to design a unified solution to minimize task execution time under different MTO scenarios.
Debunking Free Fusion Myth: Online Multi-view Anomaly Detection with Disentangled Product-of-Experts Modeling
Multi-view or even multi-modal data is appealing yet challenging for real-world applications.
Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment
Anomaly segmentation plays a pivotal role in identifying atypical objects in images, crucial for hazard detection in autonomous driving systems.
DDRF: Denoising Diffusion Model for Remote Sensing Image Fusion
Denosing diffusion model, as a generative model, has received a lot of attention in the field of image generation recently, thanks to its powerful generation capability.
PPCR: Learning Pyramid Pixel Context Recalibration Module for Medical Image Classification
Spatial attention mechanism has been widely incorporated into deep convolutional neural networks (CNNs) via long-range dependency capturing, significantly lifting the performance in computer vision, but it may perform poorly in medical imaging.
U2Net: A General Framework with Spatial-Spectral-Integrated Double U-Net for Image Fusion
The U2Net utilizes a spatial U-Net and a spectral U-Net to extract spatial details and spectral characteristics, which allows for the discriminative and hierarchical learning of features from diverse images.
Hyperspectral Image Super-Resolution
Image Super-Resolution
+1
Rethinking Spatial Invariance of Convolutional Networks for Object Counting
We evaluate our methods on 4 mainstream object counting networks (i. e., MCNN, CSRNet, SANet, and ResNet-50).
Ranked #1 on
Object Counting
on TRANCOS
SIT: A Bionic and Non-Linear Neuron for Spiking Neural Network
Spiking Neural Networks (SNNs) have piqued researchers' interest because of their capacity to process temporal information and low power consumption.
Solve routing problems with a residual edge-graph attention neural network
In this paper, an end-to-end deep reinforcement learning framework is proposed to solve this type of combinatorial optimization problems.
Dynamic Cross Feature Fusion for Remote Sensing Pansharpening
In order to enhance the relationships of inter-branches, dynamic cross feature transfers are embedded into multiple branches to obtain high-resolution representations.
Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting
By minimizing the mutual information, each column is guided to learn features with different image scales.
Learning Spatial Awareness to Improve Crowd Counting
Although the Maximum Excess over SubArrays (MESA) loss has been previously proposed to address the above issues by finding the rectangular subregion whose predicted density map has the maximum difference from the ground truth, it cannot be solved by gradient descent, thus can hardly be integrated into the deep learning framework.
Ranked #5 on
Crowd Counting
on WorldExpo’10
Adversarial Multimodal Network for Movie Question Answering
In AMN, as inspired by generative adversarial networks, we propose to learn multimodal feature representations by finding a more coherent subspace for video clips and the corresponding texts (e. g., subtitles and questions).
Optimizing Interim Analysis Timing for Bayesian Adaptive Commensurate Designs
In developing products for rare diseases, statistical challenges arise due to the limited number of patients available for participation in drug trials and other clinical research.
Applications Computation Methodology
Matching on Generalized Propensity Scores with Continuous Exposures
We apply our proposed method to estimate the average causal exposure-response function between long-term PM$_{2. 5}$ exposure and all-cause mortality among 68. 5 million Medicare enrollees, 2000-2016.
Methodology Applications
Perceiving Physical Equation by Observing Visual Scenarios
To tackle this challenge, we present a novel pipeline comprised of an Observer Engine and a Physicist Engine by respectively imitating the actions of an observer and a physicist in the real world.
Video2Shop: Exact Matching Clothes in Videos to Online Shopping Images
For the video side, deep visual features are extracted from detected object regions in each frame, and further fed into a Long Short-Term Memory (LSTM) framework for sequence modeling, which captures the temporal dynamics in videos.
On the Selection of Anchors and Targets for Video Hyperlinking
A principle way of hyperlinking can be carried out by picking centers of clusters as anchors and from there reach out to targets within or outside of clusters with consideration of neighborhood complexity.
Causal inference in the context of an error prone exposure: air pollution and mortality
We propose a new approach for estimating causal effects when the exposure is measured with error and confounding adjustment is performed via a generalized propensity score (GPS).
Methodology Applications
Memory-Augmented Attribute Manipulation Networks for Interactive Fashion Search
We introduce a new fashion search protocol where attribute manipulation is allowed within the interaction between users and search engines, e. g. manipulating the color attribute of the clothing from red to blue.
Multi-View Image Generation from a Single-View
This paper addresses a challenging problem -- how to generate multi-view cloth images from only a single view input.
Diversified Visual Attention Networks for Fine-Grained Object Classification
Fine-grained object classification is a challenging task due to the subtle inter-class difference and large intra-class variation.
