Search Results for author:
Found 17 papers, 6 papers with code
Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey
Consequently, understanding the methods of jailbreak attacks and existing defense mechanisms is essential to ensure the safe deployment of multimodal generative models in real-world scenarios, particularly in security-sensitive applications.
Online Multi-Label Classification under Noisy and Changing Label Distribution
Motivated by this, we propose an online multi-label classification algorithm under Noisy and Changing Label Distribution (NCLD).
Deep Learning Technology for Face Forgery Detection: A Survey
This paper presents a comprehensive survey of recent deep learning-based approaches for facial forgery detection.
Generative Iris Prior Embedded Transformer for Iris Restoration
In this work, we propose a generative iris prior embedded Transformer model (Gformer), in which we build a hierarchical encoder-decoder network employing Transformer block and generative iris prior.
MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
Current multimodal misinformation detection (MMD) methods often assume a single source and type of forgery for each sample, which is insufficient for real-world scenarios where multiple forgery sources coexist.
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
Specifically, semantic guidance is derived by establishing a semantic editing direction based on reasoned intentions, while quality guidance is achieved through classifier guidance using an image fidelity discriminator.
StableGarment: Garment-Centric Generation via Stable Diffusion
In this paper, we introduce StableGarment, a unified framework to tackle garment-centric(GC) generation tasks, including GC text-to-image, controllable GC text-to-image, stylized GC text-to-image, and robust virtual try-on.
FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs
The massive generation of multimodal fake news involving both text and images exhibits substantial distribution discrepancies, prompting the need for generalized detectors.
QAGait: Revisit Gait Recognition from a Quality Perspective
Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns.
Exploring 3D-aware Lifespan Face Aging via Disentangled Shape-Texture Representations
Existing face aging methods often focus on modeling either texture aging or using an entangled shape-texture representation to achieve face aging.
AdvCloak: Customized Adversarial Cloak for Privacy Protection
This strategy initially focuses on adapting the masks to the unique individual faces via image-specific training and then enhances their feature-level generalization ability to diverse facial variations of individuals via person-specific training.
Second-order Confidence Network for Early Classification of Time Series
Existing approaches mainly utilize heuristic stopping rules to capture stopping signals from the prediction results of time series classifiers.
Ranked #1 on
Early Classification
on ECG200
Bidirectional Knowledge Reconfiguration for Lightweight Point Cloud Analysis
Directly employing small models may result in a significant drop in performance since it is difficult for a small model to adequately capture local structure and global shape information simultaneously, which are essential clues for point cloud analysis.
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification
Consequently, we propose a cross-modal ordinal pairwise loss to refine the CLIP feature space, where texts and images maintain both semantic alignment and ordering alignment.
Pluralistic Aging Diffusion Autoencoder
Face aging is an ill-posed problem because multiple plausible aging patterns may correspond to a given input.
CHATEDIT: Towards Multi-turn Interactive Facial Image Editing via Dialogue
This paper explores interactive facial image editing via dialogue and introduces the ChatEdit benchmark dataset for evaluating image editing and conversation abilities in this context.
Motion-aware Memory Network for Fast Video Salient Object Detection
Moreover, inspired by the boundary supervision commonly used in image salient object detection (ISOD), we design a motion-aware loss for predicting object boundary motion and simultaneously perform multitask learning for VSOD and object motion prediction, which can further facilitate the model to extract spatiotemporal features accurately and maintain the object integrity.
