🍓Material-Aware Grouping🍓

👉Material Magic Wand (Adobe) is a tool for material-aware grouping of parts in untextured 3D meshes. Given one selected part, it automatically retrieves the other parts in the same shape by its material. Repo announced💙

👉Review https://t.ly/q00SU
👉Paper https://arxiv.org/pdf/2603.17370
👉Project umangi-jain.github.io/material-magic-wand/
👉Repo TBA

🦪OccAny: Universal 3D Occupancy🦪

👉OccAny by Valeo is a novel unified framework for generalized unconstrained urban 3D occupancy prediction. Repo under Apache 2.0💙

👉Review https://t.ly/FFiU0
👉Paper https://arxiv.org/pdf/2603.23502
👉Project https://valeoai.github.io/OccAny/
👉Repo https://github.com/valeoai/OccAny

🐍Pose-Appearance-Motion for HOI🐍

👉PAM is a novel Pose–Appearance–Motion Engine for controllable Hand–Object Interaction SOTA video generation. Repo/models available💙

👉Review https://t.ly/JU4MD
👉Paper arxiv.org/pdf/2603.22193
👉Project gasaiyu.github.io/PAM.github.io/
👉Repo https://github.com/GasaiYU/PAM

💥 GaussianGPT 3D GSC💥

👉From TUM, GaussianGPT: transformer-based 3D Gaussians generation via next-token prediction -> full 3D complex indoor scene. Repo announced💙

👉Review https://t.ly/bj-lL
👉Paper arxiv.org/pdf/2603.26661
👉Project nicolasvonluetzow.github.io/GaussianGPT/
👉Repo TBA

👌HandX: Scaling Hands Motion👌

👉 HandX is a unified foundation spanning data, annotation, and evaluation: novel large-scale dataset of bimanual & dexterous motions with fine-grained textual. Around 6M frames. Repo available💙

👉Review https://t.ly/1nGxw
👉Paper https://arxiv.org/pdf/2603.28766
👉Project https://handx-project.github.io/
👉Repo github.com/handx-project/HandX

🌵SOTA Training-Free In-Context Segmentation🌵

👉INSID3 is the new SOTA, training-free approach that segments concepts at varying granularities only from frozen DINOv3 features, given an in-context example. Repo under Apache 2.0💙

👉Review https://t.ly/NVWHN
👉Paper arxiv.org/pdf/2603.28480
👉Project visinf.github.io/INSID3/
👉Repo github.com/visinf/INSID3

🪬Camera Raw Image Generation🪬

👉RawGen by #Samsung is a generative approach that learns the complex distribution of raw sensor data directly, enabling high-fidelity generation from either text descriptions or standard sRGB images across arbitrary camera sensors. Linear raw image once, then apply any ISP operation. Repo announced💙

👉Review https://t.ly/_QVKP
👉Paper https://arxiv.org/pdf/2604.00093
👉Project https://dy112.github.io/rawgen-page/
👉Repo TBA

🍎Video Object Deletion🍎

👉Void by Netflix is a novel video object removal framework designed to perform physically-plausible inpainting in very complex scenarios. Repo under Apache 2.0💙

👉Review https://t.ly/cMVny
👉Paper https://arxiv.org/pdf/2604.02296
👉Project https://void-model.github.io/
👉Repo https://github.com/Netflix/void-model

🔥Vanast: VTON w/ Human Animation🔥

👉SNU unveils a novel unified framework that generates garment-transferred human animation videos directly from a single human/garment images, and pose guidance clip. Repo announced💙

👉Review https://t.ly/c0t79
👉Paper arxiv.org/pdf/2604.04934
👉Project hyunsoocha.github.io/vanast/
👉Repo github.com/snuvclab/vanast

🔥BoxerNet: SOTA 2D->3D BBs🔥

👉Boxer by META: transformer-based network to lift 2D BB proposals into 3D, followed by multi-view fusion and geometric filtering to produce globally consistent de-duplicated 3DBBs in metric world space. Repo under A-NC 4.0 International💙

👉Review https://t.ly/mlmV1
👉Paper https://arxiv.org/pdf/2604.05212
👉Project facebookresearch.github.io/boxer/
👉Repo github.com/facebookresearch/boxer

Hinton our guest in Pavia (remotely) 💚😈

Would you see a clip about the interview?

Here the preview, tomorrow the full clip from official source :)