Papers with Code 아카이브
Image Manipulation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 2
Image Manipulation is the process of altering or transforming an existing image to achieve a desired effect or to modify its content. This can involve various techniques and tools to enhance, modify, or create images based on specific requirements.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MaskGIT: Masked Generative Image Transformer
Crowd-powered Face Manipulation Detection: Fusing Human Examiner Decisions
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN
Feature transforms for image data augmentation
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?
Learning Hierarchical Graph Representation for Image Manipulation Detection
GMFIM: A Generative Mask-guided Facial Image Manipulation Model for Privacy Preservation
LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned Image Manipulation
MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection
TAFIM: Targeted Adversarial Attacks against Facial Image Manipulations
High Fidelity Visualization of What Your Self-Supervised Representation Knows About
A Unified Architecture of Semantic Segmentation and Hierarchical Generative Adversarial Networks for Expression Manipulation
HyperInverter: Improving StyleGAN Inversion via Hypernetwork
SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches
EdiBERT, a generative model for image editing
Sound-Guided Semantic Image Manipulation
Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model
Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation
Analysing Statistical methods for Automatic Detection of Image Forgery
Application of deep learning to camera trap data for ecologists in planning / engineering -- Can captivity imagery train a model which generalises to the wild?
Simple but Effective: CLIP Embeddings for Embodied AI
Seamless Satellite-image Synthesis
StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation
Unpaired Learning for High Dynamic Range Image Tone Mapping
FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces
Seamless Copy Move Manipulation in Digital Images
Flow Plugin Network for conditional generation
DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
High-Fidelity GAN Inversion for Image Attribute Editing
Image Shape Manipulation from a Single Augmented Training Sample
Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization
Towards Controllable and Photorealistic Region-wise Image Manipulation
TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.