Soumitri Chattopadhyay ✈️ #WACV2026

Sharing a life milestone... Graduated from Jadavpur University (Bachelor of Engineering, Information Technology) batch of 2019-2023! These past 4 years have undoubtedly been the best time of my life... it has been an absolute pleasure to be a part of the JU family! #graJUated

BMVC 2024 proceedings are now online! bmvc2024.org

@RamanDutt4 draw.io for me all the way!

Dear X community, what’s the best tool to make figures for academic AI papers? I am tired of using PowerPoint 🥱

@neelinc @qatarairways Faced a similar situation back in 2022 while flying from Montreal to Kolkata. Baggage arrived two days later, were delivered to home. The first flight was delayed and they didn't have enough time to board the luggage for the second flight. Hope you all get your baggage soon :)

Appalled at @qatarairways Baggage services. Flew from Kolkata to New York baggages didnt arrive. Flew back from Dallas to Kolkata, Baggage did not arrive. We had concerts and intruments did not come. Disgusting and very very dissapointing. #AnjanDutt #AmytDatta

The culture of “sports” does not require a world champion. It requires awareness and enthusiasm. Growing up in 80s/90s in Kolkata, there were specialized chess clubs like Alekhine Chess Club, chess tournaments at school level, and this wasn’t just confined to Kolkata, but to mofussil towns. This wasn’t a 80s phenomenon either. Chess was played through generations by kings and nobles, and yes that’s what “sporting culture” means. As a point of reference, India had cricketing culture for decades before it won the World Cup in 83.

#Hindus were silent when #Halal prasadam offered in HRCE controlled temple in TN, reports came that Sabarimala prasadam had halal jaggery. Now we face the most disgusting case of beef tallow, lard and veg oil found in #TirumalaLaddu. Only solution - #ScrapHRCE. Free our faith😠

Unfortunately won't be attending #CVPR24 but please check out our papers 1. MeLFusion: schowdhury671.github.io/melfusion_cvpr… 2. VistaLLM: shramanpramanick.github.io/VistaLLM/ Both of these are Poster Highlights! #CVPR24 #GenerativeAI

@swarnaNLP Congratulations Swarna da!! It's been a pleasure interacting with you, getting advice about PhD life, and would really miss your presence in the department. Super proud of you😎 and wish you all the best for your future 🎉🎉 (and hope you come to CH again some time :P)

🥳 I've graduated w/ my thesis on "Interpretable+structured models for multi-step reasoning". Thanks to my advisor @mohitban47 & @uncnlp for the awesome PhD experience 🙏 Next: Excited to announce I'll join FAIR Labs @AIatMeta to continue research on reasoning w/ @jaseweston 😃

6th January 2008, India loose to Australia in a very controversial test match at Sydney . Harbhajan Singh was almost banned from 2 tests (due to Monkey Gate) and India were on the verge of pulling out of the series. Amidst of all these things India were scheduled to play Australia in the third test in Perth, this was India’s chance for redemption not only terms of levelling the series but in terms getting back the pride. (Thread)

এটা চলচ্চিত্রের গল্প, এটা মৃণালের গল্প। Thank you অঞ্জন দত্ত & @neelinc for trusting us with this gem. Presenting the official poster of #ChaalchitraEkhon, Anjan Dutt's tribute to #MrinalSen in his centenary year | Film in cinemas 10th May, only in selected theatres and simultaneously @hoichoitv @SVFsocial

Join the T4V 2024 Workshop for the latest research developments in Transformers, multimodal learning and related areas!

Come check out our workshop this year at CVPR 2024, and also submit any interesting papers you might care to share to a very large and interested audience! Deadline is 4/15, just enough time if you start soon. :-)

The 3rd Transformers for Vision workshop will be back at #CVPR2024! We have a great speaker lineup covering diverse Transformer topics! Papers Due: Apr 15. Website: sites.google.com/view/t4v-cvpr24 Organized w/ @_rohitgirdhar_, @ZhidingYu, @giffmana, @gulvarol, @mohitban47 and others!

🔊Check out our preprint, AVSiam 🤝. We use a single shared ViT to process audio and visual inputs, improving its parameter efficiency⚡, reducing the GPU memory footprint💻, and allowing us to scale📈 to larger datasets and model sizes. arxiv.org/abs/2403.19638 w. @gberta227 👇

SCAMAY RAINA: A THREAD

🚨 #BMVC2024 Update 🚨
Attention researchers and innovators! We heard you and acted on it! The paper submission deadline has been extended to May 10th, 2024! The submission portal will open from April 1st!💡📚
#BMVC2024 #MachineLearning #ComputerVision #DeadlineExtended

🚨 Can a VidQA model train on continually arriving datasets effectively and efficiently adapt to time distribution shifts? We propose DAM, which shows impressing adaptability to various VidQA domains (9.1% better Acc) while mitigating catastrophic forgetting (1.9% less forget).

Modern VidQA models are static, operating on fixed training datasets. In contrast, real-world applications demand adaptability to continually changing training domains. We present a parameter-efficient method for continual VidQA learning. arxiv.org/abs/2403.08755 🧵

ML research is following the exact same trend now, tweak fast and preprint just to beat others!! The number of preprints are skyrocketing while we still feel like we aren’t learning anything new while every question seems to be answered. Can we slow down on publications and try to build expertise? (On the other hand, companies don’t even interview unless you trained a large-scale diffusion model or an LLM right now! Can’t blame the grad students🤷‍♀️) #rant #phdlife #MachineLearning

Video ReCap Recursive Captioning of Hour-Long Videos Most video captioning models are designed to process short video clips of few seconds and output text describing low-level visual concepts (e.g., objects, scenes, atomic actions). However, most real-world videos last for minutes or hours and have a complex hierarchical structure spanning different temporal granularities. We propose Video ReCap, a recursive video captioning model that can process video inputs of dramatically different lengths (from 1 second to 2 hours) and output video captions at multiple hierarchy levels. The recursive video-language architecture exploits the synergy between different video hierarchies and can process hour-long videos efficiently. We utilize a curriculum learning training scheme to learn the hierarchical structure of videos, starting from clip-level captions describing atomic actions, then focusing on segment-level descriptions, and concluding with generating summaries for hour-long videos. Furthermore, we introduce Ego4D-HCap dataset by augmenting Ego4D with 8,267 manually collected long-range video summaries. Our recursive model can flexibly generate captions at different hierarchy levels while also being useful for other complex video understanding tasks, such as VideoQA on EgoSchema.