← Generation
Computer Vision › Generation ›

Image Generation

4128 directly classified papers

Papers per year

Papers

CookGAN: Causality Based Text-to-Image Synthesis CVPR 2020
SketchyCOCO: Image Generation From Freehand Scene Sketches CVPR 2020
Learning a Neural 3D Texture Space From 2D Exemplars CVPR 2020
Wish You Were Here: Context-Aware Human Generation CVPR 2020
3D Photography Using Context-Aware Layered Depth Inpainting CVPR 2020
Semantically Multi-Modal Image Synthesis CVPR 2020
EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning CVPR 2020
Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning CVPR 2020
Generating 3D People in Scenes Without People CVPR 2020
Nested Scale-Editing for Conditional Image Synthesis CVPR 2020
StarGAN v2: Diverse Image Synthesis for Multiple Domains CVPR 2020
StyleRig: Rigging StyleGAN for 3D Control Over Portrait Images CVPR 2020
One-Shot Domain Adaptation for Face Generation CVPR 2020
Learning Fused Pixel and Feature-Based View Reconstructions for Light Fields CVPR 2020
Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision CVPR 2020
Unpaired Image Super-Resolution Using Pseudo-Supervision CVPR 2020
Active 3D Motion Visualization Based on Spatiotemporal Light-Ray Integration CVPR 2020
Learning Texture Transformer Network for Image Super-Resolution CVPR 2020
RiFeGAN: Rich Feature Generation for Text-to-Image Synthesis From Prior Knowledge CVPR 2020
Learning Part Generation and Assembly for Structure-Aware Shape Synthesis AAAI 2020
Unpaired Image Enhancement Featuring Reinforcement-Learning-Controlled Image Editing Software AAAI 2020
The Missing Data Encoder: Cross-Channel Image Completion with Hide-and-Seek Adversarial Network AAAI 2020
Ultrafast Photorealistic Style Transfer via Neural Architecture Search AAAI 2020
InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models AAAI 2020
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks AAAI 2020