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Found 17 papers, 2 papers with code
MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation
Few-shot instance segmentation extends the few-shot learning paradigm to the instance segmentation task, which tries to segment instance objects from a query image with a few annotated examples of novel categories.
Multilingual Communication System with Deaf Individuals Utilizing Natural and Visual Languages
To bridge this language barrier, we propose a novel multilingual communication system, namely MUGCAT, to improve the communication efficiency of sign language users.
Analysis of Master Vein Attacks on Finger Vein Recognition Systems
The results raise the alarm about the robustness of such systems and suggest that master vein attacks should be considered an important security measure.
Rethinking Adversarial Examples for Location Privacy Protection
We have investigated a new application of adversarial examples, namely location privacy protection against landmark recognition systems.
Robust Deepfake On Unrestricted Media: Generation And Detection
Recent advances in deep learning have led to substantial improvements in deepfake generation, resulting in fake media with a more realistic appearance.
Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently
Deep neural networks are vulnerable to adversarial examples (AEs), which have adversarial transferability: AEs generated for the source model can mislead another (target) model's predictions.
GUNNEL: Guided Mixup Augmentation and Multi-View Fusion for Aquatic Animal Segmentation
Recent years have witnessed great advances in object segmentation research.
Effectiveness of Detection-based and Regression-based Approaches for Estimating Mask-Wearing Ratio
However, there is still a lack of comprehensive research on both methodologies and datasets.
OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wild
To promote these new tasks, we have created the first large-scale dataset posing a high level of challenges that is designed with face-wise rich annotations explicitly for face forgery detection and segmentation, namely OpenForensics.
Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation
For human instance, we develop skeleton-guided segmentation in a frame along with object flow to correct and refine the result across frames.
Anabranch Network for Camouflaged Object Segmentation
Different from existing networks for segmentation, our proposed network possesses the second branch for classification to predict the probability of containing camouflaged object(s) in an image, which is then fused into the main branch for segmentation to boost up the segmentation accuracy.
Ranked #9 on
Camouflaged Object Segmentation
on CAMO
Fashion-Guided Adversarial Attack on Person Segmentation
It generates adversarial textures learned from fashion style images and then overlays them on the clothing regions in the original image to make all persons in the image invisible to person segmentation networks.
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite
We also provide a benchmark suite for the task of camouflaged instance segmentation.
MirrorNet: Bio-Inspired Camouflaged Object Segmentation
Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the mirror stream corresponding with the original image and its flipped image, respectively.
Ranked #3 on
Camouflaged Object Segmentation
on CAMO
Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation
In addition, to tackle the task of VSSIS, we augment the DAVIS-2017 benchmark dataset by assigning semantic ground-truth for salient instance labels, obtaining SEmantic Salient Instance Video (SESIV) dataset.
Video Salient Object Detection Using Spatiotemporal Deep Features
STCRF is our extension of CRF to the temporal domain and describes the relationships among neighboring regions both in a frame and over frames.
Region-Based Multiscale Spatiotemporal Saliency for Video
Detecting salient objects from a video requires exploiting both spatial and temporal knowledge included in the video.
