Search Results for author:
Found 28 papers, 8 papers with code
A4O: All Trigger for One sample
Based on this correlation, we propose reducing the magnitude of each trigger type and combining them to achieve a strong backdoor relying on the combined trigger while still staying safely under the radar of defenders.
REM: A Scalable Reinforced Multi-Expert Framework for Multiplex Influence Maximization
In social online platforms, identifying influential seed users to maximize influence spread is a crucial as it can greatly diminish the cost and efforts required for information dissemination.
Innovative Silicosis and Pneumonia Classification: Leveraging Graph Transformer Post-hoc Modeling and Ensemble Techniques
This paper presents a comprehensive study on the classification and detection of Silicosis-related lung inflammation.
Enhancing Fine-grained Image Classification through Attentive Batch Training
Fine-grained image classification, which is a challenging task in computer vision, requires precise differentiation among visually similar object categories.
SwiftEdit: Lightning Fast Text-Guided Image Editing via One-Step Diffusion
Recent advances in text-guided image editing enable users to perform image edits through simple text inputs, leveraging the extensive priors of multi-step diffusion-based text-to-image models.
SNOOPI: Supercharged One-step Diffusion Distillation with Proper Guidance
However, our study reveals its instability when handling different diffusion model backbones due to using a fixed guidance scale within the Variational Score Distillation (VSD) loss.
Any3DIS: Class-Agnostic 3D Instance Segmentation by 2D Mask Tracking
Existing 3D instance segmentation methods frequently encounter issues with over-segmentation, leading to redundant and inaccurate 3D proposals that complicate downstream tasks.
SwiftBrush v2: Make Your One-step Diffusion Model Better Than Its Teacher
Remarkably, by combining the weights of models trained with efficient LoRA and full training, we achieve a new state-of-the-art one-step diffusion model, achieving an FID of 8. 14 and surpassing all GAN-based and multi-step Stable Diffusion models.
Open-Ended 3D Point Cloud Instance Segmentation
To mitigate this constraint, we propose a novel problem termed Open-Ended 3D Instance Segmentation (OE-3DIS), which eliminates the necessity for predefined class names during testing.
MetaAug: Meta-Data Augmentation for Post-Training Quantization
The transformation network modifies the original calibration data and the modified data will be used as the training set to learn the quantized model with the objective that the quantized model achieves a good performance on the original calibration data.
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
Bayesian Neural Networks (BNNs) offer probability distributions for model parameters, enabling uncertainty quantification in predictions.
Driver Attention Tracking and Analysis
This network has a camera calibration module that can compute an embedding vector that represents the spatial configuration between the driver and the camera system.
FlexEdit: Flexible and Controllable Diffusion-based Object-centric Image Editing
Our work addresses limitations seen in previous approaches for object-centric editing problems, such as unrealistic results due to shape discrepancies and limited control in object replacement or insertion.
Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains
This algorithm works by transforming a blurry input image, which is challenging to deblur, into another blurry image that is more amenable to deblurring.
Frequency Attention for Knowledge Distillation
Inspired by the benefits of the frequency domain, we propose a novel module that functions as an attention mechanism in the frequency domain.
OpenSUN3D: 1st Workshop Challenge on Open-Vocabulary 3D Scene Understanding
This report provides an overview of the challenge hosted at the OpenSUN3D Workshop on Open-Vocabulary 3D Scene Understanding held in conjunction with ICCV 2023.
EFHQ: Multi-purpose ExtremePose-Face-HQ dataset
The existing facial datasets, while having plentiful images at near frontal views, lack images with extreme head poses, leading to the downgraded performance of deep learning models when dealing with profile or pitched faces.
Count What You Want: Exemplar Identification and Few-shot Counting of Human Actions in the Wild
To develop and evaluate our approach, we introduce a diverse and realistic dataset consisting of real-world data from 37 subjects and 50 action categories, encompassing both sensor and audio data.
Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidance
We introduce Open3DIS, a novel solution designed to tackle the problem of Open-Vocabulary Instance Segmentation within 3D scenes.
Ranked #1 on
3D Open-Vocabulary Instance Segmentation
on S3DIS
3D Instance Segmentation
3D Open-Vocabulary Instance Segmentation
+4
Stable Messenger: Steganography for Message-Concealed Image Generation
In the ever-expanding digital landscape, safeguarding sensitive information remains paramount.
Virtual Fusion with Contrastive Learning for Single Sensor-based Activity Recognition
Various types of sensors can be used for Human Activity Recognition (HAR), and each of them has different strengths and weaknesses.
Ranked #1 on
Human Activity Recognition
on PAMAP2
(Accuracy metric)
Federated Few-shot Learning for Cough Classification with Edge Devices
In this work, our aim is to develop a framework that can effectively perform cough classification even in situations when enormous cough data is not available, while also addressing privacy concerns.
UnsMOT: Unified Framework for Unsupervised Multi-Object Tracking with Geometric Topology Guidance
In this paper, we push forward the state-of-the-art performance of unsupervised MOT methods by proposing UnsMOT, a novel framework that explicitly combines the appearance and motion features of objects with geometric information to provide more accurate tracking.
HyperCUT: Video Sequence from a Single Blurry Image using Unsupervised Ordering
We consider the challenging task of training models for image-to-video deblurring, which aims to recover a sequence of sharp images corresponding to a given blurry image input.
QC-StyleGAN -- Quality Controllable Image Generation and Manipulation
The network can synthesize various image degradation and restore the sharp image via a quality control code.
Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks
Knowledge distillation which learns a lightweight student model by distilling knowledge from a cumbersome teacher model is an attractive approach for learning compact deep neural networks (DNNs).
Personalized breath based biometric authentication with wearable multimodality
To be more specific, we design new hardware which consists of an acoustic sensor to collect audio features from the nose, as well as an accelerometer and gyroscope to collect movement on the chest as a result of an individual's breathing.
Goal scoring in Premier League with Poisson regression
Premier League is known as one of the most competitive football league in the world, hence there are many goals are scored here every match.
