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Found 14 papers, 7 papers with code
Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks
Diffusion models trained on large-scale datasets have achieved remarkable progress in image synthesis.
Recasting Regional Lighting for Shadow Removal
Based on this observation, we propose to condition the restoration of attenuated textures on the corrected local lighting in the shadow region.
Towards Self-Adaptive Pseudo-Label Filtering for Semi-Supervised Learning
In this work, we observe that the distribution gap between the confidence values of correct and incorrect pseudo labels emerges at the very beginning of the training, which can be utilized to filter pseudo labels.
Neural Preset for Color Style Transfer
In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed.
BiFormer: Vision Transformer with Bi-Level Routing Attention
As the core building block of vision transformers, attention is a powerful tool to capture long-range dependency.
Ranked #9 on
Object Detection
on COCO 2017
(mAP metric)
Structure-Informed Shadow Removal Networks
Hence, in this paper, we propose to remove shadows at the image structure level.
Harmonizer: Learning to Perform White-Box Image and Video Harmonization
Unlike prior methods that are based on black-box autoencoders, Harmonizer contains a neural network for filter argument prediction and several white-box filters (based on the predicted arguments) for image harmonization.
Ranked #7 on
Image Harmonization
on iHarmony4
MODNet-V: Improving Portrait Video Matting via Background Restoration
In this work, we observe that instead of asking the user to explicitly provide a background image, we may recover it from the input video itself.
Modal Uncertainty Estimation via Discrete Latent Representations
Many important problems in the real world don't have unique solutions.
Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting
These two phenomenons reveal that deep shadow detectors heavily depend on the intensity cue, which we refer to as intensity bias.
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition
MODNet is easy to be trained in an end-to-end manner.
Ranked #1 on
Image Matting
on PPM-100
Towards Geometry Guided Neural Relighting with Flash Photography
By incorporating the depth map, our approach is able to extrapolate realistic high-frequency effects under novel lighting via geometry guided image decomposition from the flashlight image, and predict the cast shadow map from the shadow-encoding transformed depth map.
Guided Collaborative Training for Pixel-wise Semi-Supervised Learning
Although SSL methods have achieved impressive results in image classification, the performances of applying them to pixel-wise tasks are unsatisfactory due to their need for dense outputs.
Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning
In this work, we show that the coupled EMA teacher causes a performance bottleneck.
Semi-Supervised Image Classification
Unsupervised Domain Adaptation
