Search Results for author:
Found 23 papers, 14 papers with code
WildFake: A Large-scale Challenging Dataset for AI-Generated Images Detection
2) Hierarchical structure: WildFake contains fake images synthesized by different types of generators from GANs, diffusion models, to other generative models.
ComFusion: Personalized Subject Generation in Multiple Specific Scenes From Single Image
Recent advancements in personalizing text-to-image (T2I) diffusion models have shown the capability to generate images based on personalized visual concepts using a limited number of user-provided examples.
Progressive Painterly Image Harmonization from Low-level Styles to High-level Styles
Painterly image harmonization aims to harmonize a photographic foreground object on the painterly background.
Painterly Image Harmonization by Learning from Painterly Objects
In particular, we learn a mapping from background style and object information to object style based on painterly objects in artistic paintings.
Boosting Audio-visual Zero-shot Learning with Large Language Models
Audio-visual zero-shot learning aims to recognize unseen categories based on paired audio-visual sequences.
Ranked #1 on
GZSL Video Classification
on ActivityNet-GZSL (cls)
Painterly Image Harmonization via Adversarial Residual Learning
In this work, we employ adversarial learning to bridge the domain gap between foreground feature map and background feature map.
ControlCom: Controllable Image Composition using Diffusion Model
To address these challenges, we propose a controllable image composition method that unifies four tasks in one diffusion model: image blending, image harmonization, view synthesis, and generative composition.
Shadow Generation with Decomposed Mask Prediction and Attentive Shadow Filling
Specifically, in the first stage, we decompose shadow mask prediction into box prediction and shape prediction.
WeditGAN: Few-Shot Image Generation via Latent Space Relocation
In this work, we introduce WeditGAN, which realizes model transfer by editing the intermediate latent codes $w$ in StyleGANs with learned constant offsets ($\Delta w$), discovering and constructing target latent spaces via simply relocating the distribution of source latent spaces.
Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation
First, we train a data-efficient StyleGAN2 on defect-free images as the backbone.
Painterly Image Harmonization in Dual Domains
In this work, we propose a novel painterly harmonization network consisting of a dual-domain generator and a dual-domain discriminator, which harmonizes the composite image in both spatial domain and frequency domain.
Marine Microalgae Detection in Microscopy Images: A New Dataset
The total number of images in the dataset is 937 and all the objects in these images were annotated.
SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification
Contrastive loss ensures the transferable semantic directions are class-irrelevant and mode seeking loss is adopted to produce diverse tail-class features and enlarge the feature space of tail classes.
Ranked #29 on
Long-tail Learning
on CIFAR-10-LT (ρ=10)
Few-shot Image Generation Using Discrete Content Representation
Few-shot image translation disentangles an image into style vector and content map.
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
In this work, we propose a novel Delta Generative Adversarial Network (DeltaGAN), which consists of a reconstruction subnetwork and a generation subnetwork.
Defending Graph Neural Networks via Tensor-Based Robust Graph Aggregation
In this paper, we propose a tensor-based framework for GNNs to learn robust graphs from adversarial graphs by aggregating predefined robust graphs to enhance the robustness of GNNs via tensor approximation.
Large-Scale Adversarial Attacks on Graph Neural Networks via Graph Coarsening
Graph Neural Networks (GNNs) are fragile to adversarial attacks.
Making Images Real Again: A Comprehensive Survey on Deep Image Composition
We have also contributed the first image composition toolbox: libcom https://github. com/bcmi/libcom, which assembles 10+ image composition related functions (e. g., image blending, image harmonization, object placement, shadow generation, generative composition).
Shadow Generation for Composite Image in Real-world Scenes
In this work, we focus on generating plausible shadow for the foreground object in the composite image.
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
In this work, we propose a novel Delta Generative Adversarial Network (DeltaGAN), which consists of a reconstruction subnetwork and a generation subnetwork.
F2GAN: Fusing-and-Filling GAN for Few-shot Image Generation
In this paper, we propose a Fusing-and-Filling Generative Adversarial Network (F2GAN) to generate realistic and diverse images for a new category with only a few images.
Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets
To address these issues, we propose our MTL with Selective Augmentation (MTL-SA) method to select the training samples in unlabeled datasets with confident pseudo labels and close data distribution to the labeled dataset.
MatchingGAN: Matching-based Few-shot Image Generation
Matching generator can match random vectors with a few conditional images from the same category and generate new images for this category based on the fused features.
