VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning
Salient object detection (SOD) and camouflaged object detection (COD) are related yet
distinct binary mapping tasks. These tasks involve multiple modalities sharing …
distinct binary mapping tasks. These tasks involve multiple modalities sharing …
[HTML][HTML] Improving existing segmentators performance with zero-shot segmentators
This paper explores the potential of using the SAM (Segment-Anything Model) segmentator
to enhance the segmentation capability of known methods. SAM is a promptable …
to enhance the segmentation capability of known methods. SAM is a promptable …
VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks
We present VisionLLM v2, an end-to-end generalist multimodal large model (MLLM) that
unifies visual perception, understanding, and generation within a single framework. Unlike …
unifies visual perception, understanding, and generation within a single framework. Unlike …
Training Spatial-Frequency Visual Prompts and Probabilistic Clusters for Accurate Black-Box Transfer Learning
Despite the growing prevalence of black-box pre-trained models (PTMs) such as prediction
API services, there remains a significant challenge in directly applying general models to …
API services, there remains a significant challenge in directly applying general models to …
Towards Real Zero-Shot Camouflaged Object Segmentation without Camouflaged Annotations
C Lei, J Fan, X Li, T Xiang, A Li, C Zhu… - arXiv preprint arXiv …, 2024 - arxiv.org
Camouflaged Object Segmentation (COS) faces significant challenges due to the scarcity of
annotated data, where meticulous pixel-level annotation is both labor-intensive and costly …
annotated data, where meticulous pixel-level annotation is both labor-intensive and costly …
ForgeryTTT: Zero-Shot Image Manipulation Localization with Test-Time Training
Social media is increasingly plagued by realistic fake images, making it hard to trust content.
Previous algorithms to detect these fakes often fail in new, real-world scenarios because …
Previous algorithms to detect these fakes often fail in new, real-world scenarios because …
A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet
closely-related computer vision tasks widely studied during the past decades. Though …
closely-related computer vision tasks widely studied during the past decades. Though …
GFHANet: Global Feature Hybrid Attention Network for Salient Object Detection in Side-Scan Sonar Images
SA Yuan, Z Wang, FL He, SW Zhang, ZY Zhao - IEEE Access, 2024 - ieeexplore.ieee.org
With the wide application of deep learning in image processing, salient object detection
(SOD) in underwater sonar images has become an important research topic. However, due …
(SOD) in underwater sonar images has become an important research topic. However, due …
DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions
Semantic segmentation in adverse weather scenarios is a critical task for autonomous
driving systems. While foundation models have shown promise, the need for specialized …
driving systems. While foundation models have shown promise, the need for specialized …
External Prompt Features Enhanced Parameter-Efficient Fine-Tuning for Salient Object Detection
Salient object detection (SOD) aims at finding the most salient objects in images and outputs
pixel-level binary masks. Transformer-based methods achieve promising performance due …
pixel-level binary masks. Transformer-based methods achieve promising performance due …