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Found 25 papers, 13 papers with code
PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a Unified Framework
Generating aesthetic posters is more challenging than simple design images: it requires not only precise text rendering but also the seamless integration of abstract artistic content, striking layouts, and overall stylistic harmony.
MMGT: Motion Mask Guided Two-Stage Network for Co-Speech Gesture Video Generation
Specifically, we propose a Motion Mask-Guided Two-Stage Network (MMGT) that uses audio, as well as motion masks and motion features generated from the audio signal to jointly drive the generation of synchronized speech gesture videos.
UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache
In this paper, we propose an efficient visual transformer framework for ultra-high-definition (UHD) image dehazing that addresses the key challenges of slow training speed and high memory consumption for existing methods.
Black-box Adversaries from Latent Space: Unnoticeable Attacks on Human Pose and Shape Estimation
These findings underscore the urgent need to address and mitigate security risks associated with digital human generation systems.
DSDNet: Raw Domain Demoiréing via Dual Color-Space Synergy
To address these limitations, we propose a single-stage raw domain demoir\'eing framework, Dual-Stream Demoir\'eing Network (DSDNet), which leverages the synergy of raw and YCbCr images to remove moir\'e while preserving luminance and color fidelity.
NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images.
JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restoration
Vision-centric perception systems often struggle with unpredictable and coupled weather degradations in the wild.
Modality-Fair Preference Optimization for Trustworthy MLLM Alignment
To address this, we propose Modality-Fair Preference Optimization (MFPO) to balance text and image preferences.
Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation
ColorCode offers three key features: 1) color enhancement, producing an enhanced image with a fixed color; 2) color adaptation, enabling controllable adjustments of long-wavelength color components using guidance images; and 3) color interpolation, allowing for the smooth generation of multiple colors through continuous sampling of the color code.
Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removal
There are 5, 442 daytime raindrop images and 9, 744 nighttime raindrop images.
UCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt
Compressed Image Super-resolution (CSR) aims to simultaneously super-resolve the compressed images and tackle the challenging hybrid distortions caused by compression.
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models
Recent advancements in general-purpose or domain-specific multimodal large language models (LLMs) have witnessed remarkable progress for medical decision-making.
Joint Visual and Text Prompting for Improved Object-Centric Perception with Multimodal Large Language Models
In this paper, we present a novel approach, Joint Visual and Text Prompting (VTPrompt), that employs fine-grained visual information to enhance the capability of MLLMs in VQA, especially for object-oriented perception.
How Powerful Potential of Attention on Image Restoration?
Our designs provide a closer look at the attention mechanism and reveal that some simple operations can significantly affect the model performance.
NightHaze: Nighttime Image Dehazing via Self-Prior Learning
By increasing the noise values to approach as high as the pixel intensity values of the glow and light effect blended images, our augmentation becomes severe, resulting in stronger priors.
SeD: Semantic-Aware Discriminator for Image Super-Resolution
In particular, one discriminator is utilized to enable the SR network to learn the distribution of real-world high-quality images in an adversarial training manner.
Polyp-DAM: Polyp segmentation via depth anything model
In this paper, we unfold a new perspective on polyp segmentation modeling by leveraging the Depth Anything Model (DAM) to provide depth prior to polyp segmentation models.
NightRain: Nighttime Video Deraining via Adaptive-Rain-Removal and Adaptive-Correction
However, the intricacies of the real world, particularly with the presence of light effects and low-light regions affected by noise, create significant domain gaps, hampering synthetic-trained models in removing rain streaks properly and leading to over-saturation and color shifts.
Ranked #2 on
Rain Removal
on Nightrain
Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution
In this paper, we enhance the visibility from a single nighttime haze image by suppressing glow and enhancing low-light regions.
Estimating Reflectance Layer from A Single Image: Integrating Reflectance Guidance and Shadow/Specular Aware Learning
To further enforce the reflectance layer to be independent of shadows and specularities in the second-stage refinement, we introduce an S-Aware network that distinguishes the reflectance image from the input image.
DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity
Most existing methods rely on binary shadow masks, without considering the ambiguous boundaries of soft and self shadows.
Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal
Few existing image defogging or dehazing methods consider dense and non-uniform particle distributions, which usually happen in smoke, dust and fog.
Ranked #2 on
Nonhomogeneous Image Dehazing
on NH-HAZE validation
DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network
To address the problem, in this paper, we propose an unsupervised domain-classifier guided shadow removal network, DC-ShadowNet.
Ranked #3 on
Shadow Removal
on SRD
Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression
To address this problem, we need to suppress the light effects in bright regions while, at the same time, boosting the intensity of dark regions.
Ranked #36 on
Low-Light Image Enhancement
on LOL
