Search Results for author:
Found 51 papers, 29 papers with code
GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing
The proposed hazing method does not rely on the atmosphere scattering model, and we provide an explanation as to why it is not necessarily beneficial to take advantage of the dimension reduction offered by the atmosphere scattering model for image dehazing, even if only the dehazing results on synthetic images are concerned.
Ranked #4 on
Image Dehazing
on RS-Haze
End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation
Video super-resolution aims at generating a high-resolution video from its low-resolution counterpart.
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments
Motivation Identifying compound–protein interaction (CPI) is a crucial task in drug discovery and chemogenomics studies, and proteins without three-dimensional structure account for a large part of potential biological targets, which requires developing methods using only protein sequence information to predict CPI.
Ranked #2 on
Drug Discovery
on LIT-PCBA(ESR1_ant)
AWNet: Attentive Wavelet Network for Image ISP
In this paper, we introduce a novel network that utilizes the attention mechanism and wavelet transform, dubbed AWNet, to tackle this learnable image ISP problem.
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
Extensive experiments demonstrate that owing to the informativeness of the camera raw data, the effectiveness of the network architecture, and the separation of super-resolution and color correction processes, the proposed method achieves superior VSR results compared to the state-of-the-art and can be adapted to any specific camera-ISP.
Video Frame Interpolation via Generalized Deformable Convolution
Video frame interpolation aims at synthesizing intermediate frames from nearby source frames while maintaining spatial and temporal consistencies.
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results.
Learning for Unconstrained Space-Time Video Super-Resolution
Recent years have seen considerable research activities devoted to video enhancement that simultaneously increases temporal frame rate and spatial resolution.
Optical Flow Estimation
Space-time Video Super-resolution
+2
PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization
To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations.
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing
We also propose a novel intra-task knowledge transfer mechanism that can memorize and take advantage of synthetic domain knowledge to assist the learning process on the translated data.
Towards a Unified Approach to Single Image Deraining and Dehazing
We develop a new physical model for the rain effect and show that the well-known atmosphere scattering model (ASM) for the haze effect naturally emerges as its homogeneous continuous limit.
Video Frame Interpolation Transformer
Existing methods for video interpolation heavily rely on deep convolution neural networks, and thus suffer from their intrinsic limitations, such as content-agnostic kernel weights and restricted receptive field.
Sound Adversarial Audio-Visual Navigation
In this work, we design an acoustically complex environment in which, besides the target sound, there exists a sound attacker playing a zero-sum game with the agent.
SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments
Traditional biological and pharmaceutical manufacturing plants are controlled by human workers or pre-defined thresholds.
Pay Self-Attention to Audio-Visual Navigation
Audio-visual embodied navigation, as a hot research topic, aims training a robot to reach an audio target using egocentric visual (from the sensors mounted on the robot) and audio (emitted from the target) input.
Self adaptive global-local feature enhancement for radiology report generation
Automated radiology report generation aims at automatically generating a detailed description of medical images, which can greatly alleviate the workload of radiologists and provide better medical services to remote areas.
Online Streaming Video Super-Resolution with Convolutional Look-Up Table
To facilitate the research on this problem, a new benchmark dataset named LDV-WebRTC is constructed based on a real-world online streaming system.
VDPVE: VQA Dataset for Perceptual Video Enhancement
Few researchers have specifically proposed a video quality assessment method for video enhancement, and there is also no comprehensive video quality assessment dataset available in public.
A Perceptual Quality Assessment Exploration for AIGC Images
\underline{AI} \underline{G}enerated \underline{C}ontent (\textbf{AIGC}) has gained widespread attention with the increasing efficiency of deep learning in content creation.
Hierarchical Fine-Grained Image Forgery Detection and Localization
As a result, the algorithm is encouraged to learn both comprehensive features and inherent hierarchical nature of different forgery attributes, thereby improving the IFDL representation.
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancement
To this end, we first construct a Low-Light Video Enhancement Quality Assessment (LLVE-QA) dataset in which 254 original low-light videos are collected and then enhanced by leveraging 8 LLVE algorithms to obtain 2, 060 videos in total.
Cheap-fake Detection with LLM using Prompt Engineering
We enhance the baseline algorithm by incorporating a Large Language Model (LLM), GPT3. 5, as a feature extractor.
AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment
With the rapid advancements of the text-to-image generative model, AI-generated images (AGIs) have been widely applied to entertainment, education, social media, etc.
TransMRSR: Transformer-based Self-Distilled Generative Prior for Brain MRI Super-Resolution
We perform a generative task to encapsulate diverse priors into a generative network (GAN), which is the decoder sub-module of the deep non-local feature capture part, in the first stage.
Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluation
To address this gap, we propose SJTU-H3D, a subjective quality assessment database specifically designed for full-body digital humans.
NTIRE 2023 Quality Assessment of Video Enhancement Challenge
61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions.
IvyGPT: InteractiVe Chinese pathwaY language model in medical domain
General large language models (LLMs) such as ChatGPT have shown remarkable success.
RAWIW: RAW Image Watermarking Robust to ISP Pipeline
To achieve end-to-end training of the framework, we integrate a neural network that simulates the ISP pipeline to handle the RAW-to-RGB conversion process.
StableVQA: A Deep No-Reference Quality Assessment Model for Video Stability
Indeed, most existing quality assessment models evaluate video quality as a whole without specifically taking the subjective experience of video stability into consideration.
FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Table
Experimental results on benchmark datasets demonstrate that our method achieves the State-Of-The-Art (SOTA) performance in terms of both image quality and inter-frame brightness consistency.
FLAME-based Multi-View 3D Face Reconstruction
Our work mainly addresses the problem of combining parametric models of faces with multi-view face 3D reconstruction and explores the implementation of a Flame based multi-view training and testing framework for contributing to the field of face 3D reconstruction.
AccFlow: Backward Accumulation for Long-Range Optical Flow
To train and evaluate the proposed AccFlow, we have constructed a large-scale high-quality dataset named CVO, which provides ground-truth optical flow labels between adjacent and distant frames.
TCM-GPT: Efficient Pre-training of Large Language Models for Domain Adaptation in Traditional Chinese Medicine
To the best of our knowledge, our study represents the pioneering validation of domain adaptation of a large language model with 7 billion parameters in TCM domain.
A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification
Although current data augmentation methods are successful to alleviate the data insufficiency, conventional augmentation are primarily intra-domain while advanced generative adversarial networks (GANs) generate images remaining uncertain, particularly in small-scale datasets.
A Comprehensive Dataset and Automated Pipeline for Nailfold Capillary Analysis
In this study, we present a pioneering effort in constructing a comprehensive nailfold capillary dataset-321 images, 219 videos from 68 subjects, with clinic reports and expert annotations-that serves as a crucial resource for training deep-learning models.
Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models
Recent advancements in Multi-modality Large Language Models (MLLMs) have demonstrated remarkable capabilities in complex high-level vision tasks.
Distance Guided Generative Adversarial Network for Explainable Binary Classifications
Experimental results show that DisGAN consistently outperforms the GAN-based augmentation methods with explainable binary classification.
Q-Refine: A Perceptual Quality Refiner for AI-Generated Image
With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge.
AttentionLut: Attention Fusion-based Canonical Polyadic LUT for Real-time Image Enhancement
Subsequently, the attention fusion module integrates the image feature with the priori attention feature obtained during training to generate image-adaptive canonical polyadic tensors.
Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey
Large-scale pre-trained vision models (PVMs) have shown great potential for adaptability across various downstream vision tasks.
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic.
Towards Open-ended Visual Quality Comparison
Comparative settings (e. g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardizes the evaluation criteria across different observers and offer more clear-cut responses.
Resolution-Agnostic Neural Compression for High-Fidelity Portrait Video Conferencing via Implicit Radiance Fields
In this paper, we propose a novel low bandwidth neural compression approach for high-fidelity portrait video conferencing using implicit radiance fields to achieve both major objectives.
Text2QR: Harmonizing Aesthetic Customization and Scanning Robustness for Text-Guided QR Code Generation
This approach harnesses the potent generation capabilities of stable-diffusion models, navigating the trade-off between image aesthetics and QR code scannability.
Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment
Based on T2VQA-DB, we propose a novel transformer-based model for subjective-aligned Text-to-Video Quality Assessment (T2VQA).
AIGCOIQA2024: Perceptual Quality Assessment of AI Generated Omnidirectional Images
Finally, we conduct a benchmark experiment to evaluate the performance of state-of-the-art IQA models on our database.
AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment
With the rapid advancements in AI-Generated Content (AIGC), AI-Generated Images (AIGIs) have been widely applied in entertainment, education, and social media.
Perception-Oriented Video Frame Interpolation via Asymmetric Blending
In practice, motion estimates often prove to be error-prone, resulting in misaligned features.
THQA: A Perceptual Quality Assessment Database for Talking Heads
In the realm of media technology, digital humans have gained prominence due to rapid advancements in computer technology.
