- TimeLens: Event-based Video Clip Frame Interpolation
- Diverse Generation from just one Video Clip Made Possible
- Competent Rain Nowcasting using Deep Generative Types Of Radar
- The Beverage Hand Difficulties: Three-Stem Acoustics Separation for Real-World Soundtracks
- ADOP: Rough Differentiable One-Pixel Point Rendering
- (Style)CLIPDraw: Coupling material and Style in Text-to-Drawing Synthesis
- SwinIR: picture recovery using swin transformer
- EditGAN: High-Precision Semantic Graphics Modifying
- CityNeRF: Building NeRF at Area Measure
OpenAI effectively trained a system in a position to establish files from text captions. It can be similar to GPT-3 and Image GPT and brings incredible outcomes.
Bing utilized a customized StyleGAN2 design to generate an internet fitting place where you could immediately try-on any trousers or t-shirts you prefer only using a graphic of your self.
Will Transformers Upgrade CNNs in Computer Sight?
Tl;DR: They blended the results of GANs and convolutional methods with all the expressivity of transformers to produce an effective and time-efficient means for semantically-guided top-notch graphics synthesis.
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