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Found 14 papers, 4 papers with code
Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration
In this work, we address the limitations of denoising diffusion models (DDMs) in image restoration tasks, particularly the shape and color distortions that can compromise image quality.
PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models
To this end, we extend each image into a "static" video and introduce a unified token compression strategy called Progressive Visual Token Compression (PVC), where the tokens of each frame are progressively encoded and adaptively compressed to supplement the information not extracted from previous frames.
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
Recently, vision model pre-training has evolved from relying on manually annotated datasets to leveraging large-scale, web-crawled image-text data.
ReWiTe: Realistic Wide-angle and Telephoto Dual Camera Fusion Dataset via Beam Splitter Camera Rig
The fusion of images from dual camera systems featuring a wide-angle and a telephoto camera has become a hotspot problem recently.
View Transition based Dual Camera Image Fusion
Our insight is to minimize the occlusion area and thus maximize the use of pixels from $\bf{T}$ images.
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image Denoising
Based on the prior that, for each pixel, its similar pixels are usually spatially close, our insights are that (1) we partition the image into non-overlapped windows and perform regional self-attention to reduce the search range of each pixel, and (2) we encourage pixels across different windows to communicate with each other.
MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems
In most of the related HDR imaging methods, the problem is usually solved by Multiple Images Merging, i. e. the final HDR image is fused from pixels of all the input LDR images.
A Pyramid Recurrent Network for Predicting Crowdsourced Speech-Quality Ratings of Real-World Signals
The real-world capabilities of objective speech quality measures are limited since current measures (1) are developed from simulated data that does not adequately model real environments; or they (2) predict objective scores that are not always strongly correlated with subjective ratings.
Cycle-CNN for Colorization towards Real Monochrome-Color Camera Systems
We present a new CNN model, named cycle CNN, which can directly use the real data from monochrome-color camera systems for training.
Learning a Deep Convolutional Network for Colorization in Monochrome-Color Dual-Lens System
To get high-quality color images, it is desired to colorize the gray image with the color image as reference.
Chain of Reasoning for Visual Question Answering
A chain of reasoning (CoR) is constructed for supporting multi-step and dynamic reasoning on changed relations and objects.
Ground-truth dataset and baseline evaluations for image base-detail separation algorithms
Base-detail separation is a fundamental computer vision problem consisting of modeling a smooth base layer with the coarse structures, and a detail layer containing the texture-like structures.
Fidelity-Naturalness Evaluation of Single Image Super Resolution
In this paper, we proposed to use both fidelity (the difference with original images) and naturalness (human visual perception of super resolved images) for evaluation.
Region-Based Temporally Consistent Video Post-Processing
We study the problem of temporally consistent video post-processing.
