Detecting camouflaged object in frequency domain
Camouflaged object detection (COD) aims to identify objects that are perfectly embedded in
their environment, which has various downstream applications in fields such as medicine …
their environment, which has various downstream applications in fields such as medicine …
Tcnet: Co-salient object detection via parallel interaction of transformers and cnns
Y Ge, Q Zhang, TZ Xiang, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The purpose of co-salient object detection (CoSOD) is to detect the salient objects that co-
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
occur in a group of relevant images. CoSOD has been significantly prospered by recent …
Toward stable co-saliency detection and object co-segmentation
In this paper, we present a novel model for simultaneous stable co-saliency detection
(CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) …
(CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) …
Highly efficient natural image matting
Over the last few years, deep learning based approaches have achieved outstanding
improvements in natural image matting. However, there are still two drawbacks that impede …
improvements in natural image matting. However, there are still two drawbacks that impede …
Scene Matters: Model-based Deep Video Compression
Video compression has always been a popular research area, where many traditional and
deep video compression methods have been proposed. These methods typically rely on …
deep video compression methods have been proposed. These methods typically rely on …
FINet: Frequency Injection Network for Lightweight Camouflaged Object Detection
W Liang, J Wu, Y Wu, X Mu, J Xu - IEEE Signal Processing …, 2024 - ieeexplore.ieee.org
Existing camouflaged object detection (COD) methods typically have large model
parameters and computations, hindering their deployment in real-world applications …
parameters and computations, hindering their deployment in real-world applications …
Vqnerv: Vector quantization neural representation for video compression
The application of Implicit Neural Representations (INR) for video compression represents
an evolving area of research. Despite its potential, conventional CNN-based INR methods …
an evolving area of research. Despite its potential, conventional CNN-based INR methods …
HM-PCGC: A Human-Machine Balanced Point Cloud Geometry Compression Scheme
Point cloud compression has various purposes in different application scenarios, such as
requiring visual fidelity in human vision tasks and pursuing semantic fidelity in machine …
requiring visual fidelity in human vision tasks and pursuing semantic fidelity in machine …
Predicting 360° Video Saliency: A ConvLSTM Encoder-Decoder Network with Spatio-temporal Consistency
360° videos have been widely used with the development of virtual reality technology and
triggered a demand to determine the most visually attractive objects in them, aka 360° video …
triggered a demand to determine the most visually attractive objects in them, aka 360° video …
Rethinking two-B-real net for real-time salient object detection
Exploring a fast and accurate salient object detection (SOD) model is a promising research
area. TBRS [1] has been proposed a two-branch network for real-time SOD. However, its …
area. TBRS [1] has been proposed a two-branch network for real-time SOD. However, its …