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Found 35 papers, 20 papers with code
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration
Recent progress in generative models has significantly improved image restoration capabilities, particularly through powerful diffusion models that offer remarkable recovery of semantic details and local fidelity.
Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers
To address this, we propose DiffCR, a dynamic DiT inference framework with differentiable compression ratios, which automatically learns to dynamically route computation across layers and timesteps for each image token, resulting in efficient DiTs.
UniReal: Universal Image Generation and Editing via Learning Real-world Dynamics
We introduce UniReal, a unified framework designed to address various image generation and editing tasks.
Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation and Reconstruction
Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency.
Improved physics-informed neural network in mitigating gradient related failures
Physics-informed neural networks (PINNs) integrate fundamental physical principles with advanced data-driven techniques, driving significant advancements in scientific computing.
Brush2Prompt: Contextual Prompt Generator for Object Inpainting
Object inpainting is a task that involves adding objects to real images and seamlessly compositing them.
Perceptual Artifacts Localization for Image Synthesis Tasks
Recent advancements in deep generative models have facilitated the creation of photo-realistic images across various tasks.
SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network
In photo editing, it is common practice to remove visual distractions to improve the overall image quality and highlight the primary subject.
Automatic High Resolution Wire Segmentation and Removal
In this paper, we present an automatic wire clean-up system that eases the process of wire segmentation and removal/inpainting to within a few seconds.
Image as Set of Points
Context clusters (CoCs) view an image as a set of unorganized points and extract features via simplified clustering algorithm.
Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators
Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects.
Keys to Better Image Inpainting: Structure and Texture Go Hand in Hand
We claim that the performance of inpainting algorithms can be better judged by the generated structures and textures.
Perceptual Artifacts Localization for Inpainting
Inspired by this workflow, we propose a new learning task of automatic segmentation of inpainting perceptual artifacts, and apply the model for inpainting model evaluation and iterative refinement.
Towards Layer-wise Image Vectorization
Image rasterization is a mature technique in computer graphics, while image vectorization, the reverse path of rasterization, remains a major challenge.
GeoFill: Reference-Based Image Inpainting with Better Geometric Understanding
Our approach achieves state-of-the-art performance on both RealEstate10K and MannequinChallenge dataset with large baselines, complex geometry and extreme camera motions.
Image Super-Resolution With Non-Local Sparse Attention
NLSA is designed to retain long-range modeling capability from NL operation while enjoying robustness and high-efficiency of sparse representation.
TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations
Image inpainting is the task of plausibly restoring missing pixels within a hole region that is to be removed from a target image.
Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels
Retinal vessel segmentation from retinal images is an essential task for developing the computer-aided diagnosis system for retinal diseases.
Ranked #2 on
Retinal Vessel Segmentation
on CHASE_DB1
High-Resolution Deep Image Matting
Image matting is a key technique for image and video editing and composition.
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results
The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration.
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
By combining the new CS-NL prior with local and in-scale non-local priors in a powerful recurrent fusion cell, we can find more cross-scale feature correlations within a single low-resolution (LR) image.
Ranked #11 on
Image Super-Resolution
on Manga109 - 3x upscaling
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
This challenge is based on a newly collected validation and testing image datasets, and hence, named SIDD+.
Pyramid Attention Networks for Image Restoration
Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales.
Image Restoration for Under-Display Camera
The new trend of full-screen devices encourages us to position a camera behind a screen.
MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion Recognition
Spatial-temporal feature learning is of vital importance for video emotion recognition.
FLNet: Landmark Driven Fetching and Learning Network for Faithful Talking Facial Animation Synthesis
In this paper, We present a landmark driven two-stream network to generate faithful talking facial animation, in which more facial details are created, preserved and transferred from multiple source images instead of a single one.
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising.
When AWGN-based Denoiser Meets Real Noises
In this paper, we propose a novel approach to boost the performance of a real image denoiser which is trained only with synthetic pixel-independent noise data dominated by AWGN.
Ranked #2 on
Denoising
on Darmstadt Noise Dataset
GeoNet: Deep Geodesic Networks for Point Cloud Analysis
Surface-based geodesic topology provides strong cues for object semantic analysis and geometric modeling.
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
Upon our SSG, we further introduce a clustering-guided semisupervised approach named SSG ++ to conduct the one-shot domain adaption in an open set setting (i. e. the number of independent identities from the target domain is unknown).
Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features
The integration of information across multiple modalities and across time is a promising way to enhance the emotion recognition performance of affective systems.
Survey of Face Detection on Low-quality Images
However, previous proposed models are mostly trained and tested on good-quality images which are not always the case for practical applications like surveillance systems.
Unsupervised Representation Adversarial Learning Network: from Reconstruction to Generation
The newly proposed RepGAN is tested on MNIST, fashionMNIST, CelebA, and SVHN datasets to perform unsupervised classification, generation and reconstruction tasks.
Horizontal Pyramid Matching for Person Re-identification
Despite the remarkable recent progress, person re-identification (Re-ID) approaches are still suffering from the failure cases where the discriminative body parts are missing.
Ranked #59 on
Person Re-Identification
on DukeMTMC-reID
Photorealistic Facial Expression Synthesis by the Conditional Difference Adversarial Autoencoder
It handles the problem of disambiguating changes due to identity and changes due to facial expression by learning to generate the difference between low-level features of images of the same person but with different facial expressions.
