Assistant Professor @BristolUni | Past: PhD & Postdoc @InfAtEd @EdinburghUni. Postdoc @MMLab, CUHK

Bristol
Joined March 2017
Wei-Hong Li retweeted
It is the *best* time to start your own research group in AI @bristolcs Why? 🌟 Bristol hosts the largest supercomputer in the UK - Isambard AI, 4th greenest in the world. 🧑‍🎓 New undergrad degree CS w AI &multiple masters 6⃣Nov DL to apply for position, Link in 🧵
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Wei-Hong Li retweeted
It was a great week @eccvconf #ECCV2026 #Malmo for current members of the group and catching up with alumni! Here's a group pic missing a few, @prajwal_gatti @Sid__Bansal @JacobChalkie @ahmad_darkhalil @zhifan_zhu @_alexstergiou @chiaraplizzari &Kevin, Toby, Evangelos.
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Wei-Hong Li retweeted
Just arriving into Copenhagen on our way to Malmo for @eccvconf #ECCV2026 with current and some ex faces @bristolcs #MaVi
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Wei-Hong Li retweeted
Our #ECCV2026 @eccvconf paper Gen2Balance: Generative Balancing for Long-Tailed Video Action Recognition now on ArXiv w/ code&data&models prajwalgatti.github.io/gen2b… Can we fill imbalanced action recognition datasets with generative images to outperform long-tail SOTA? Yes we can 🧵
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Wei-Hong Li retweeted
Fun fact: the apartment we rented in Oxford Summertown from 2021-2023 has accommodated @elliottszwu (CVPR20 best paper awardee) and @jianyuan_wang (CVPR25 best paper awardee) as subletters. Now also @ChuhanZhang5 - new CVPR26 best paper awardee. Grateful to be at @Oxford_VGG !!
Huge congrats to the team, D4RT is a team work and all the authors have been working very hard on this in the past one year. Very well deserved. 🍻 and thank you Award Committee Members for the recognition.
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I’m looking for a PhD student with UK home fee status to join my lab at Cambridge starting this October. If you’re interested and have research experience in multimodal spatial modeling or vision-based robot learning, email me your CV. Funding deadline is approaching very soon.
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Wei-Hong Li retweeted
Special thanks @_atewari @Cambridge_Eng for visiting us @BristolUni @bristolcs for a great #MaVi Seminar on "Physical Inductive Biases for World Models" and your thoughtful 1-1s with the researchers. Have a good trip back to Cambridge and please visit us again soon,
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Wei-Hong Li retweeted
📢 Preprint Prime and Reach: Synthesising Body Motion for Gaze-Primed Object Reach arxiv.org/abs/2512.16456 masashi-hatano.github.io/pri… First work to synthesise the natural behavior of full-body priming (i.e. gazing towards) an object b4 reaching - curated from 5 public datasets. 1/3
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Wei-Hong Li retweeted
Preprint 📢 The N-Body Problem: Parallel Execution from Single-Person Egocentric Video Input: Single-person egocentric video 👤 Out: imagine how these tasks can be performed faster by N > 1 people, correctly 👥 📎arxiv.org/abs/2512.11393 👀zhifanzhu.github.io/ego-nbod… 1/4
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Wei-Hong Li retweeted
Super-exciting talk by @anikembhavi @wayve_ai at @BristolUni #MaVi Seminar @bristolcs today! World models for evaluating autonomous driving, GAIA evolution w GAIA3 released! End-to-end driving model &loads of insights! Thanks for visiting &spending the day talking to researchers
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Excited to be at #NeurIPS 2025 San Diego in person from 1st - 8th Dec! DM me for meeting/coffee chat about #image_editing, #video_understanding, #WorldModels and #RL for common research interests, potential collaboration, startup ideas ... See you in San Diego⛴️! ! Also welcome tour, city walk, common game interests ......
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If you are looking for a PhD position, Elliott’s group is an excellent choice. He offers not just cutting-edge research directions and impactful tasks but also detailed plans, constructive feedback, and personalized mentorship. These are all you need to grow as a researcher
I'm looking for two PhD students to join our team at Cambridge to work on 3D/4D modeling in various domains including generative media, robotics, and biology. Apply to the PhD in Engineering program by December 2 ⌛️: postgraduate.study.cam.ac.uk…
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Wei-Hong Li retweeted
📢 New Paper PointSt3R: Point Tracking through 3D Grounded Correspondence Can point tracking be re-formulated as pairwise frame correspondence solely? We fine-tuning MASt3R with dynamic correspondences and a visibility loss and achieve competitive point tracking results 1/3
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Wei-Hong Li retweeted
Many thanks 2 Francois Bremond (@inria_sophia) for a 2-day #Bristol visit @BristolUni #MaVi (Machine Learning &Computer Vision) research group hosted by @WayHomeLi. Great presentation incl. #CVPR2025 & #ICCV2025 papers from Francois's group, insights and future directions. 1/2
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🚀 The next generation of AI models must go beyond creating pixels - it needs to build and understand worlds. At SpAItial, we're developing foundation models that are physically grounded by design. Excited to share what we've been building with an incredible team!
🚀🚀🚀Announcing our $13M funding round to build the next generation of AI: 𝐒𝐩𝐚𝐭𝐢𝐚𝐥 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐌𝐨𝐝𝐞𝐥𝐬 that can generate entire 3D environments anchored in space & time. 🚀🚀🚀 Interested? Join our world-class team: 🌍 spaitial.ai #GenAI #3DAI
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Build what you need and use what you build. This is a core philosophy of my research. It shifts the focus away from publishing “papers” to what really matters — impact. This thread unpacks why I think this is a successful approach to science. 1/10 Or see: perceiving-systems.blog/en/p…
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Wei-Hong Li retweeted
🎉 Excited to share Clarity, an open-source website template I designed to better present and visualise AI research! If you appreciate the minimalist design and want to use it in your own projects, please check it out here: shikun.io/projects/clarity
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Why are reps converging? We suggest a few possibilities, including: As we train on more tasks, there are fewer reps that can satisfy all, leading to an Anna Karenina scenario (arxiv.org/abs/2106.07682): all strong models are alike, each weak model is weak in its own way. 3/8
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Wei-Hong Li retweeted
We are releasing 4M-21 with a permissive license, including its source code and trained models. It's a pretty effective multimodal model that solves 10s of tasks & modalities. See the demo code, sample results, and the tokenizers of diverse modalities on the website. IMO, the multitask learning aspect of multimodal models has really taken a step forward. We can train a single model on many diverse tasks with ~SOTA accuracy. But a long way to go in terms of transfer/emergence. 🌐 4m.epfl.ch/ ⌨️ github.com/apple/ml-4m/ Joint work w/ @EPFL_en @Apple.
We are releasing the 1st version of 4M, a framework for training multimodal foundation models across tens of modalities & tasks, based on scalable masked modeling. Joint effort by @EPFL_en & @Apple. 4M: Massively Multimodal Masked Modeling 🌐4m.epfl.ch 🧵1/n
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