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- Hyperspectral Image Classification With Attention-Aided CNNs340
An attention-aided CNN model based on the traditional CNN model that incorporates attention modules to aid networks that focus on more discriminative channels or positions for spectral and spatial classifications of hyperspectral images is proposed.
- Multiscale Point Cloud Geometry Compression268
This paper proposes a multiscale end-to-end learning framework that hierarchically reconstructs the 3D Point Cloud Geometry (PCG) via progressive re-sampling on top of a sparse convolution based autoencoder for point cloud compression and reconstruction.
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- Sparse Tensor-Based Multiscale Representation for Point Cloud Geometry Compression221
A unified Point Cloud Geometry compression method through the processing of multiscale sparse tensor-based voxelized PCG that not only shows state-of-the-art performance in both lossless and lossy compression modes across a variety of datasets, but also has low complexity which is attractive to practical applications.
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- CompGS: Efficient 3D Scene Representation via Compressed Gaussian Splatting133
An efficient 3D scene representation, named Compressed Gaussian Splatting (CompGS), which harnesses compact Gaussian primitives for faithful 3D scene modeling with a remarkably reduced data size and develops a rate-constrained optimization scheme to eliminate redundancies.
- An Efficient Four-Parameter Affine Motion Model for Video Coding114
A simplified affine motion model-based coding framework to overcome the limitation of a translational motion model and maintain low-computational complexity is studied.
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- Pseudo-Sequence-Based 2-D Hierarchical Coding Structure for Light-Field Image Compression101
The experimental results demonstrate that the proposed novel pseudo-sequence based 2-D hierarchical structure can achieve maximum 14.2% bit-rate savings compared with the state-of-the-art light-field image compression method.
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- Asymmetric color cryptosystem using chaotic Ushiki map and equal modulus decomposition in fractional Fourier transform domains74
The Ushiki chaotic system is performed to generate the random phase mask in FrFT and a random sequence for scrambling the private key in a single optical channel system to enhance the security of the proposed cryptosystem.
- Inter-Frame Compression for Dynamic Point Cloud Geometry Coding70
A deep learning-based inter-frame encoding scheme for dynamic point cloud geometry compression that predicts the latent representation of the current frame using the previous frame by employing a novel feature space inter-prediction network.
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- Early diagnosis of Parkinson's disease using Continuous Convolution Network: Handwriting recognition based on off-line hand drawing without template62
This paper studies various features of spiral hand drawing of Parkinson's disease and develops an auxiliary diagnosis scheme based on hand drawing, and Continuous Convolution Network (CC-Net) is proposed to reduce the pooling layer.
- Attribute compression of 3D point clouds using Laplacian sparsity optimized graph transform60
A new binary tree based point cloud partition is introduced and the graph signal processing tools, especially the graph transform with optimized Laplacian sparsity, are explored to achieve better energy compaction and compression efficiency.
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- PoseMapGait: A model-based gait recognition method with pose estimation maps and graph convolutional networks58
This paper exploits the byproduct of pose estimation maps, which denotes the invariant features of whole body structure and body pose joints for gait recognition, respectively, and achieves the new state-of-the-art performance compared with recent advanced model-based methods.
- Video-Based Point Cloud Compression Artifact Removal57
This work developed a novel out-of-the-loop point cloud geometry artifact removal solution that can significantly improve reconstruction quality without additional bandwidth cost and jointly recovers both the quantization direction and the quantification noise level by exploiting projection and quantization prior.
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- Multimedia Analysis, Processing and Communications54
Part I: Image Processing and Analysis, part II: Video Processing and analysis, and part III: Communications Related Processing.
- Rate-Distortion-Guided Learning Approach with Cross-Projection Information for V-PCC Fast CU Decision51
A rate-distortion-guided fast attribute coding unit (CU) partitioning approach with cross-projection information in V-PCC all-intra (AI) coding achieves the state-of-the-art performance in V -PCC AI coding.
- An Adaptive Hybrid Algorithm Based on Particle Swarm Optimization and Differential Evolution for Global Optimization51
A novel adaptive hybrid algorithm based on PSO and DE (HPSO-DE) is formulated by developing a balanced parameter between PSo and DE that is competitive with PSO, DE, and their variants.
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- Joint Video Summarization and Transmission Adaptation for Energy-Efficient Wireless Video Streaming50
This paper pursues an energy-efficient video communication solution through joint video summarization and transmission adaptation over a slow fading wireless channel and proposes a heuristic solution that has close-to-optimal performance.
- No-Reference Image Quality Assessment by Hallucinating Pristine Features48
The proposed quality assessment framework is rooted in the view that the perceptually meaningful features could be well exploited to characterize the visual quality, and the natural image statistical behaviors are exploited in an effort to deliver the accurate predictions.
- Hybrid Point Cloud Attribute Compression Using Slice-based Layered Structure and Block-based Intra Prediction48
Experimental results demonstrate that the proposed hybrid point cloud attribute compression scheme performs better than the state-of-the-art region-adaptive hierarchical transform (RAHT) system, and on average a 37.21% BD-rate gain is achieved.
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- Real-time human action recognition by luminance field trajectory analysis45
This paper presents a luminance field manifold trajectory analysis based solution for human activity recognition, without explicit object level information extraction and understanding that is computationally efficient and can operate in real time.
- A multi-stage dynamical fusion network for multimodal emotion recognition44
A multi-stage multimodal dynamical fusion network (MSMDFN), designed to split the fusion procedure into multi-stages using the correlation observed before, which allows for much more fine-grained unimodal, bimodal and trimodal intercorrelations.
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- Optical single-channel color image asymmetric cryptosystem based on hyperchaotic system and random modulus decomposition in Gyrator domains40
An enhanced optical single-channel asymmetric cryptosystem for color image is proposed by using hyperchaotic system and random modulus decomposition (RMD) in gyrator domains to increase the security of the encryption scheme and is applicable in information authentication.
- Depth-assisted calibration on learning-based factorization for a compressive light field display38
A dual-guided learning-based factorization on polarization-based CLF display with depth-assisted calibration (DAC) substantially improves the visual performance of factorization in real-time processing.
- Projection based advanced motion model for cubic mapping for 360-degree video38
A novel advanced motion model to handle the irregular motion for the cubic map projection of 360-degree video by utilizing the characteristic that most of the motions in the sphere are uniform.
- Multiscale Latent-Guided Entropy Model for LiDAR Point Cloud Compression37
A novel end-to-end, fully-factorized deep framework that represents the original LiDAR point cloud into an octree structure and hierarchically constructs the octree entropy model in layers and saves more than 99.8% of decoding time compared to previous state-of-the-art methods on LPC compression.
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- APCCPA '2233
This workshop focuses on point cloud processing, analysis-oriented optimization algorithms for compression and processing, and compression in challenging situations to further improve visual experience and machine vision performance.
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- Face De-Identification: State-of-the-Art Methods and Comparative Studies15
This survey provides a comprehensive review of state-of-the-art face de-identification methods, categorized into three levels: pixel-level, representation-level, and semantic-level techniques, demonstrating that deep learning-based approaches, particularly those using Generative Adversarial Networks and diffusion models, have achieved significant advancements in balancing privacy and utility.
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- ReGO: Reference-Guided Outpainting for Scenery Image12
ReGO (Reference-Guided Outpainting), a new method for the task of sketch-guided image outpainting that leverages neighboring reference images to synthesize texture-rich results by transferring pixels from them to facilitate texture compensating of the target image.
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- Scalable Hash From Triplet Loss Feature Aggregation For Video De-duplication6
A novel content based video segmentation identification scheme that is invariant to the underlying codec and operational bit rates is proposed, it computes robust features from a triplet loss deep learning network that captures the invariance of the same content under different coding tools and strategy, while a scalable hashing solution is developed based on Fisher Vector aggregation of the convolutional features from the Triplet loss network.
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- Multimedia Data Indexing1
In this chapter,.the.authors.discuss.the challenges.of.the.users.to.make.them.accessible.in.digital.data.management.and.capabilities.
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- An embedded application research for fingerprint pre-processing system based on TMS320VC5410 CCS 2.2–
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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