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cs.CV2024
Generating Compositional Scenes via Text-to-image RGBA Instance Generation
Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang +2
Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditio…
cs.CV2024
Improving Object Detection via Local-global Contrastive Learning
Danai Triantafyllidou, Sarah Parisot, Ales Leonardis +1
Visual domain gaps often impact object detection performance. Image-to-image translation can mitigate this effect, where contrastive approaches enable learning of the image-to-imag…
cs.CV2024
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation
Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang +5
Text-to-image generation has achieved astonishing results, yet precise spatial controllability and prompt fidelity remain highly challenging. This limitation is typically addressed…