charig yang @chaaarig
research scientist @isomorphiclabs / prev: @meta, @oxford_vgg / thai 🇹🇭 robots.ox.ac.uk/~charig Joined September 2019-
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charig yang retweeted
Reading Recognition in the Wild: A Dataset for Understanding Human Behaviors During Reading from an Egocentric Sensor Suite This large multimodal dataset features video, eye gaze, and head pose sensor outputs, created to help solve the task of reading recognition from wearable…
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charig yang retweeted
Many Congratulations to @jianyuan_wang, @MinghaoChen23, @n_karaev, Andrea Vedaldi, Christian Rupprecht and @davnov134 for winning the Best Paper Award @CVPR for "VGGT: Visual Geometry Grounded Transformer" 🥇🎉 🙌🙌 #CVPR2025!!!!!!
charig yang retweeted
SAM + Optical Flow = FlowSAM FlowSAM can discover and segment moving objects in a video and outperforms all previous approaches by a considerable margin in both single and multi-object benchmarks 🔥 robots.ox.ac.uk/~vgg/research/…
charig yang retweeted
This quote from @demishassabis is my favourite take on the "engineering vs science" debates in AI yet: AI is an engineering science: unlike in natural sciences, the phenomenon you're studying doesn't exist in nature, so you have to build it first, and then you can study.
no lights, because attention is all you need @ transformers for vision workshop #cvpr2022 (jokes aside, great talks!)
charig yang retweeted
Congratulations to @chaaarig who won best presentation and @JacksonMattT @ShreshthMalik for best poster at the Joint CDT student conference with Bristol, Lincoln and Edinburgh CDTs @aims_oxford @UniofOxford
charig yang retweeted
Temporal Alignment Networks for Long-term Video abs: arxiv.org/abs/2204.02968
charig yang retweeted
Have an idea for DALL·E? Reply with a caption. I'll generate 20 or so!
charig yang retweeted
V nice application paper! It's not just about clocks - love to see how different data sources (and their pros/cons) interact sensibly for the final system - some human data, some sim data, some "offline tracker" data. Same for Autopilot, and I expect many other applied problems.
V nice application paper! It's not just about clocks - love to see how different data sources (and their pros/cons) interact sensibly for the final system - some human data, some sim data, some "offline tracker" data. Same for Autopilot, and I expect many other applied problems.
charig yang retweeted
Some personal news: I will be joining @CompSciOxford @UniofOxford as @DeepMind chair in #AI and Fellow at @ExeterCollegeOx I owe this honour to the amazing students and collaborators with whom I have had the privilege to work during my career
Some personal news: I will be joining @CompSciOxford @UniofOxford as @DeepMind chair in #AI and Fellow at @ExeterCollegeOx I owe this honour to the amazing students and collaborators with whom I have had the privilege to work during my career
charig yang retweeted
Check out our latest work on “Segmenting Invisible Moving Objects” at @BMVCconf (w/ @WeidiXie and Andrew Zisserman) Project page: robots.ox.ac.uk/~vgg/research/…
charig yang retweeted
The new recording of Red is 2 hours long with tons of unreleased tracks added. You might even call it a … Taylor expansion
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