Search Results for author:
Found 24 papers, 7 papers with code
Task-Aware Encoder Control for Deep Video Compression
Prior research on deep video compression (DVC) for machine tasks typically necessitates training a unique codec for each specific task, mandating a dedicated decoder per task.
Noise Dimension of GAN: An Image Compression Perspective
This trade-off depicts the best divergence we can achieve when noise is limited.
Content-aware Masked Image Modeling Transformer for Stereo Image Compression
Existing learning-based stereo image codec adopt sophisticated transformation with simple entropy models derived from single image codecs to encode latent representations.
GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting
In response, we propose a groundbreaking paradigm of image representation and compression by 2D Gaussian Splatting, named GaussianImage.
Boosting Neural Representations for Videos with a Conditional Decoder
Implicit neural representations (INRs) have emerged as a promising approach for video storage and processing, showing remarkable versatility across various video tasks.
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection
In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.
Consistency Models Improve Diffusion Inverse Solvers
In addition, we propose a new family of DIS using pure CM.
Idempotence and Perceptual Image Compression
However, we find that theoretically: 1) Conditional generative model-based perceptual codec satisfies idempotence; 2) Unconditional generative model with idempotence constraint is equivalent to conditional generative codec.
Unified learning-based lossy and lossless JPEG recompression
Most image compression algorithms only consider uncompressed original image, while ignoring a large number of already existing JPEG images.
Bandwidth-efficient Inference for Neural Image Compression
With neural networks growing deeper and feature maps growing larger, limited communication bandwidth with external memory (or DRAM) and power constraints become a bottleneck in implementing network inference on mobile and edge devices.
Efficient Learned Lossless JPEG Recompression
Second, we propose pipeline parallel context model (PPCM) and compressed checkerboard context model (CCCM) for the effective conditional modeling and efficient decoding within luma and chroma components.
Conditional Perceptual Quality Preserving Image Compression
We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information.
VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection
In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.
GeneFormer: Learned Gene Compression using Transformer-based Context Modeling
Then, we propose fixed-length parallel grouping to accelerate the decoding speed of our autoregressive model.
ECM-OPCC: Efficient Context Model for Octree-based Point Cloud Compression
For octree-based point cloud compression, previous works show that the information of ancestor nodes and sibling nodes are equally important for predicting current node.
Correcting the Sub-optimal Bit Allocation
In this paper, we investigate the problem of bit allocation in Neural Video Compression (NVC).
Spatial Moment Pooling Improves Neural Image Assessment
In recent years, there has been widespread attention drawn to convolutional neural network (CNN) based blind image quality assessment (IQA).
Multi-Sample Training for Neural Image Compression
This paper considers the problem of lossy neural image compression (NIC).
Bit Allocation using Optimization
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC).
Flexible Neural Image Compression via Code Editing
Neural image compression (NIC) has outperformed traditional image codecs in rate-distortion (R-D) performance.
PO-ELIC: Perception-Oriented Efficient Learned Image Coding
In the past years, learned image compression (LIC) has achieved remarkable performance.
HLIC: Harmonizing Optimization Metrics in Learned Image Compression by Reinforcement Learning
Learned image compression is making good progress in recent years.
Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes
High-frequency ultrasound (HFU) is well suited for imaging embryonic mice due to its noninvasive and real-time characteristics.
Identification of relevant diffusion MRI metrics impacting cognitive functions using a novel feature selection method
Mild Traumatic Brain Injury (mTBI) is a significant public health problem.
