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πŸ’  Compositional Learning Journal Club

Join us this week for an in-depth discussion on Compositional Learning in the context of cutting-edge text-to-image generative models. We will explore recent breakthroughs and challenges, focusing on how these models handle compositional tasks and where improvements can be made.

βœ… This Week's Presentation:

πŸ”Ή Title: Correcting Diffusion Generation through Resampling


πŸ”Έ Presenter: Ali Aghayari

πŸŒ€ Abstract:
This paper addresses distributional discrepancies in diffusion models, which cause missing objects in text-to-image generation and reduced image quality. Existing methods overlook this root issue, leading to suboptimal results. The authors propose a particle filtering framework that uses real images and a pre-trained object detector to measure and correct these discrepancies through resampling. Their approach improves object occurrence by 5% and FID by 1.0 on MS-COCO, outperforming previous methods in generating more accurate and higher-quality images.


πŸ“„ Papers: Correcting Diffusion Generation through Resampling


Session Details:
- πŸ“… Date: Tuesday
- πŸ•’ Time: 5:30 - 6:30 PM
- 🌐 Location: Online at vc.sharif.edu/ch/rohban

We look forward to your participation! ✌️



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πŸ’  Compositional Learning Journal Club

Join us this week for an in-depth discussion on Compositional Learning in the context of cutting-edge text-to-image generative models. We will explore recent breakthroughs and challenges, focusing on how these models handle compositional tasks and where improvements can be made.

βœ… This Week's Presentation:

πŸ”Ή Title: Correcting Diffusion Generation through Resampling


πŸ”Έ Presenter: Ali Aghayari

πŸŒ€ Abstract:
This paper addresses distributional discrepancies in diffusion models, which cause missing objects in text-to-image generation and reduced image quality. Existing methods overlook this root issue, leading to suboptimal results. The authors propose a particle filtering framework that uses real images and a pre-trained object detector to measure and correct these discrepancies through resampling. Their approach improves object occurrence by 5% and FID by 1.0 on MS-COCO, outperforming previous methods in generating more accurate and higher-quality images.


πŸ“„ Papers: Correcting Diffusion Generation through Resampling


Session Details:
- πŸ“… Date: Tuesday
- πŸ•’ Time: 5:30 - 6:30 PM
- 🌐 Location: Online at vc.sharif.edu/ch/rohban

We look forward to your participation! ✌️

BY RIML Lab




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The lead from Wall Street offers little clarity as the major averages opened lower on Friday and then bounced back and forth across the unchanged line, finally finishing mixed and little changed.The Dow added 33.18 points or 0.10 percent to finish at 34,798.00, while the NASDAQ eased 4.54 points or 0.03 percent to close at 15,047.70 and the S&P 500 rose 6.50 points or 0.15 percent to end at 4,455.48. For the week, the Dow rose 0.6 percent, the NASDAQ added 0.1 percent and the S&P gained 0.5 percent.The lackluster performance on Wall Street came on uncertainty about the outlook for the markets following recent volatility.

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