Niladri Shekhar Dutt

Niladri Shekhar Dutt

@niladridutt.bsky.social

Research Intern @adobe.com | PhD @ucl.ac.uk | @ellis.eu | ex-Nvidia, Berkeley | Interested in generative modelling in vision and graphics + reasoning (LLMs) https://niladridutt.com/

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🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

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🧡9/10 We quantitaively evaluate on the Adobe5k dataset as well as conduct user studies by expert and novice users. Our evaluations show that MonetGPT outperforms open-source alternatives and performs comparably to Google Photos AutoEnhance (closed-source).

🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

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🧡8/10 Photo editing is subjective 🎨. Our framework adapts to user preference by guidance from natural language tags like β€˜vibrant’ or β€˜retro vibe’ to produce personalized and stylistically distinct retouching plans from the same input image.

🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

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🧡5/10 🧩 Puzzle B imparts aesthetic judgement. By ranking professionally edited photos against altered versions, the MLLM learns to recognize the visual characteristics of an optimally adjusted image for any given operation, building an internal aesthetic model.

🧡6/10 🧩 Puzzle C builds planning capabilities. The model learns to generate a complete, multi-step retouching plan to enhance a photo, structuring its reasoning as a sequence of discrete issues and solutions for clarity and control.

🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

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🧡3/10 Our key recipe: MLLMs struggle to predict edit values directly. We solve this by generating rich textual reasoning for each puzzle ✍️. We then fine-tune MonetGPT on this data, creating a 'reasoning pathway' that enables it to regress final adjustment values.

🧡4/10 🧩 Puzzle A builds an understanding of individual operations. The MLLM learns to map visual changes in before/after images to a specific tool and its precise parameter value, effectively learning the semantics of our procedural library.

🧡1/10 Excited to share our #SIGGRAPH paper "MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills" 🌟 We explore how to make MLLMs operation-aware by solving visual puzzles and propose a procedural framework for image retouching #MLLM

🧡2/10 MLLMs lack the visual understanding to plan edits. 🧠 So, we use expert photos as our ground truth and work backward, procedurally creating puzzles by assuming any change to an expert edit makes it less optimal

Niladri Shekhar Dutt reposted

πŸ€”What tasks do we want robots to handle? Are these preferences based on saved time or feelings we associate with the tasks? Introducing Why Automate This?β€”a study exploring automation preferences across social groups, using feelings & time-spent as key factors. πŸ‘‡ (1/5)

All the papers I've reviewed still have some reviewers who haven't participated in the discussion/replied to the rebuttal at all. This is true even after the authors have nudged the reviewers a few times already :(

ICLR Conference@iclr-conf.bsky.social

✍️ Reminder to reviewers: Check author responses to your reviews, and ask follow up questions if needed. 50% of papers have discussion - let’s bring this number up!

Niladri Shekhar Dutt reposted

Bluesky tip for newbies: Bluesky has no real algorithm. Likes here do nothing but show the poster that you enjoyed their content. That kindness is always going to be appreciated by creators, but if you want to help to boost something here, you have to repost it so others see it. πŸ™‚

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