👩‍🦱Physical-Hair Diffusion👩‍🦱

👉CONTROLHAIR is novel hybrid framework that integrates a physics simulator with conditional video diffusion to enable controllable dynamic hair rendering. Repo announced💙

👉Review https://t.ly/78LHr
👉Paper https://lnkd.in/epm-A9Fq
👉Project https://lnkd.in/evsjz298
👉Repo TBA

🔩Code-Agentic Education🔩

👉Show Lab unveils Code2Video: agentic, code-centric framework that generates HQ educational videos from knowledge points. Clarity, coherence & reproducibility. Repo under MIT💙

👉Review https://t.ly/Fv4LJ
👉Paper https://arxiv.org/pdf/2510.01174
👉Repo https://github.com/showlab/Code2Video/
👉Project https://showlab.github.io/Code2Video/

🎷🎷 Clink! Chop! Thud! 🎷🎷

👉Sounding Object Detection: while an environment may contain many objects, only a few are directly involved in producing sound during an interaction. This model detects the sounding object in a video. Code/Data announced 💙

👉Review https://t.ly/VK_1h
👉Paper https://lnkd.in/depNjVXm
👉Project https://lnkd.in/dF63EZFG
👉Repo TBA

👉 A proof I'm not a bot...

My (short) interview to one of the biggest Italian media: AI in 2016, HPC / Quantum and how I created my startup: https://www.linkedin.com/posts/visionarynet_ai-itw25-ai-activity-7381215486115643392-t7an

Thanks for the support (and of course a new paper coming in a few hours)

🎺Visual Grounding RVOS🎺

👉ReferDINO is a strong RVOS model that inherits region-level vision-language alignment from foundational visual grounding models, and is further endowed with pixel-level dense perception & cross-modal spatio-temporal reasoning. Code, Demo & checkpoints💙

👉Review https://t.ly/rOdkP
👉Paper https://lnkd.in/efuAFQdE
👉Project https://lnkd.in/dK3wMZqv
👉Repo https://lnkd.in/d3i2PsNF

💄Pixel-Perfect Depth (SOTA)💄

👉Pixel-Perfect Depth is a mono-depth estimation model with pixel-space diffusion transformers. New SOTA. Repo under Apache 2.0💙

👉Review https://t.ly/75PGo
👉Paper https://lnkd.in/d8wxFpyY
👉Project https://lnkd.in/dV5HhsqH
👉Repo https://lnkd.in/d9JKFBJq
👉Demo https://lnkd.in/d3wBkKJ9

↗️ TrackVLA++ Visual Tracking↘️

👉TrackVLA++ is a novel Vision-Language-Action model that incorporates spatial reasoning and target identification memory, enabling SOTA performance in both long-horizon and highly crowded tracking scenarios. Model announced💙

👉Review https://t.ly/ruYzc
👉Paper https://arxiv.org/pdf/2510.07134
👉Project pku-epic.github.io/TrackVLA-plus-plus-Web/
👉Repo TBA

🫧 Detect Anything via MLLM 🫧

👉Rex-Omni is a 3B-multimodal model that unifies visual perception tasks, including object detection, OCR, pointing, key-pointing & visual prompting into a single next point prediction framework. Impressive results. Repo under IDEA License 1.0💙

👉Review https://t.ly/DCTk_
👉Paper https://lnkd.in/d4VDD-9j
👉Project https://lnkd.in/d6unEyvq
👉Repo https://lnkd.in/dkYJFe-x

🫙Universal Feature Up-Sampling🫙

👉AnyUp is a novel method for feature up-sampling that can be applied to ANY vision feature at ANY resolution, without encoder-specific training: inference-time feature-agnostic up-sampling architecture to improve up-sampling quality. Repo CC-4.0💙

👉Review https://t.ly/HvEw9
👉Paper https://arxiv.org/pdf/2510.12764
👉Project https://wimmerth.github.io/anyup/
👉Repo https://github.com/wimmerth/anyup