🤖 META Human-Robot 🤖

👉#META PARTNR: novel benchmark for Planning And Reasoning Tasks in humaN-Robot collaboration. The largest benchmark of its kind: 100,000+ natural language tasks, spanning 60 houses and 5,819 unique objects. Code & Data (🤗) under MIT💙

👉Review https://t.ly/zcN0K
👉Paper arxiv.org/pdf/2411.00081
👉Repo github.com/facebookresearch/partnr-planner
🤗Data huggingface.co/datasets/ai-habitat/partnr_episodes

🖲️ VGG Transformer 🖲️

👉VGGT by VGG & #META (#CVPR2025) is a feed-forward neural net. that directly infers all key 3D attributes of a scene within seconds. Code released💙

👉Review https://t.ly/WoWXL
👉Paper https://arxiv.org/pdf/2503.11651
👉Project https://vgg-t.github.io/
👉Code github.com/facebookresearch/vggthttps://t.ly/WoWXL

🦖 DINOv3 is out 🦖

👉#Meta unveils DINOv3! A novel foundation model outperforming the previous SOTAs in computer vision. Code & weights released under DINOv3 License💙

👉Review https://t.ly/-S3ZL
👉Paper https://t.ly/ervOT
👉Project https://lnkd.in/dHFf3esd
👉Repo https://lnkd.in/dPxhDxAq
🤗HF https://lnkd.in/dWGudY2i

🫔ATLAS: SOTA Human Model🫔

👉#META presents ATLAS, a novel high-fidelity body model learned from 600k high-res. scans captured using 240 synchronized cams. Code announced, to be released💙

👉Review https://t.ly/0hHud
👉Paper arxiv.org/pdf/2508.15767
👉Project jindapark.github.io/projects/atlas/
👉Repo TBA

❤️‍🔥PHD: Personalized 3D Humans❤️‍🔥

👉ETH & #Meta unveil PHD, a novel approach for personalized 3D human mesh recovery (HMR) and body fitting that leverages user-specific shape information. Code & models to be released💙

👉Review https://t.ly/IeRhH
👉Paper https://arxiv.org/pdf/2508.21257
👉Project https://phd-pose.github.io/
👉Repo TBA

🔥 SAM 3/3D are OUT!! 🔥

👉#META released SAM 3, a unified model for detection, segmentation, tracking of objects in images & video using text, exemplar & visual prompts. Repo/Models under proprietary license💙

👉Review https://t.ly/lnRZN
👉Paper https://t.ly/5tq9N
👉Project https://ai.meta.com/sam3/
👉Demo: https://segment-anything.com
👉Repo https://github.com/facebookresearch/sam3