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Found 29 papers, 10 papers with code
AdvLoRA: Adversarial Low-Rank Adaptation of Vision-Language Models
Different from LoRA, we improve the efficiency and robustness of adversarial adaptation by designing a novel reparameterizing method based on parameter clustering and parameter alignment.
Autonomous Path Planning for Intercostal Robotic Ultrasound Imaging Using Reinforcement Learning
Ultrasound (US) has been widely used in daily clinical practice for screening internal organs and guiding interventions.
LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented Diffusion
Camouflaged vision perception is an important vision task with numerous practical applications.
Full-frequency dynamic convolution: a physical frequency-dependent convolution for sound event detection
Recently, 2D convolution has been found unqualified in sound event detection (SED).
BiHRNet: A Binary high-resolution network for Human Pose Estimation
On the challenging of COCO dataset, the proposed method enables the binary neural network to achieve 70. 8 mAP, which is better than most tested lightweight full-precision networks.
Understanding AI Cognition: A Neural Module for Inference Inspired by Human Memory Mechanisms
How humans and machines make sense of current inputs for relation reasoning and question-answering while putting the perceived information into context of our past memories, has been a challenging conundrum in cognitive science and artificial intelligence.
ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models
Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior.
Physics-constrained Attack against Convolution-based Human Motion Prediction
Specifically, we introduce a novel adaptable scheme that facilitates the attack to suit the scale of the target pose and two physical constraints to enhance the naturalness of the adversarial example.
Sparse Feedback Controller: From Open-loop Solution to Closed-loop Realization
In this paper, we explore the discrete time sparse feedback control for a linear invariant system, where the proposed optimal feedback controller enjoys input sparsity by using a dynamic linear compensator, i. e., the components of feedback control signal having the smallest possible nonzero values.
Protein Representation Learning via Knowledge Enhanced Primary Structure Modeling
Protein representation learning has primarily benefited from the remarkable development of language models (LMs).
Weakly Supervised Video Emotion Detection and Prediction via Cross-Modal Temporal Erasing Network
Automatically predicting the emotions of user-generated videos (UGVs) receives increasing interest recently.
Ranked #3 on
Video Emotion Recognition
on Ekman6
Multiple Planar Object Tracking
Specifically, we present a dual-branch network to track the visible part of planar objects, including vertexes and mask.
An end-to-end multi-scale network for action prediction in videos
Unlike most existing methods with offline feature generation, our method directly takes frames as input and further models motion evolution on two different temporal scales. Therefore, we solve the complexity problems of the two stages of modeling and the problem of insufficient temporal and spatial information of a single scale.
Robust output regulation of linear system subject to modeled and unmodeled uncertainty
The output regulation scheme is utilized in the framework to track the reference in the presence of modeled disturbance, and the effect of unmodeled disturbance is reduced by an $\mathcal{H}_\infty$ compensator.
ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image Classification
The overall framework, namely as Prototype-aware Contrastive learning (ProCo), is unified as a single-stage pipeline in an end-to-end manner to alleviate the imbalanced problem in medical image classification, which is also a distinct progress than existing works as they follow the traditional two-stage pipeline.
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images
Deformable image registration is a necessary technique for fusing multi-modal pathology slices.
Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding
Answer grounding aims to reveal the visual evidence for visual question answering (VQA), which entails highlighting relevant positions in the image when answering questions about images.
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
The first algorithm, IVIPER, extends VIPER, a recent method for single-agent interpretable RL, to the multi-agent setting.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Model-based Multi-agent Reinforcement Learning: Recent Progress and Prospects
Significant advances have recently been achieved in Multi-Agent Reinforcement Learning (MARL) which tackles sequential decision-making problems involving multiple participants.
Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition
The proposed work is the first investigation in the emotion recognition oriented EEG topological feature analysis, which brought a novel insight into the brain neural system nonlinear dynamics analysis and feature extraction.
Achieving Human Parity on Visual Question Answering
The Visual Question Answering (VQA) task utilizes both visual image and language analysis to answer a textual question with respect to an image.
Ranked #7 on
Visual Question Answering (VQA)
on VQA v2 test-dev
Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
We then design a novel FBP reconstruction loss to encourage the network to generate more perfect completion results and a residual-learning-based image refinement module to reduce the secondary artifacts in the reconstructed CT images.
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks
In Goal-oriented Reinforcement learning, relabeling the raw goals in past experience to provide agents with hindsight ability is a major solution to the reward sparsity problem.
TransCT: Dual-path Transformer for Low Dose Computed Tomography
Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radiation to patients.
Adaptive Deconvolution-based stereo matching Net for Local Stereo Matching
In deep learning-based local stereo matching methods, larger image patches usually bring better stereo matching accuracy.
Elastic Net based Feature Ranking and Selection
After features are sorted according to their frequency, linear support vector machine performs the classification in an incremental manner.
CT Super Resolution via Zero Shot Learning
We incorporated the CT domain knowledge into the SADIR and unrolled it into a DL network (SADIR Net).
Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
Computed tomography (CT) has been widely used for medical diagnosis, assessment, and therapy planning and guidance.
A Matlab Toolbox for Feature Importance Ranking
Moreover, the toolbox is evaluated on a database of 163 ultrasound images.
