AI insight - Artificial Intelligence and Deep Learning

Segment Any Motion in VideoFrom CVPR2025 a novel approach for moving object segmentation that...

🐟Segment Any Motion in Video🐟👉From CVPR2025 a novel approach for moving object segmentation that combines DINO-based semantic features and SAM2. Code under MIT license💙👉Review https://t.ly/4aYjJ👉Paper arxiv.org/pdf/2503.22268👉Project motion-seg.github.io/👉Repo github.com/nnanhuang/SegAnyMo

🌳MSVA Zero-Shot Multi-View🌳👉Niantic unveils MVSA, novel Multi-View Stereo Architecture to work anywhere by generalizing across diverse domains & depth ranges. Highly accurate & 3D-consistent depths. Code & models announced💙👉Review https://t.ly/LvuTh 👉Paper https://arxiv.org/pdf/2503.22430👉Project https://nianticlabs.github.io/mvsanywhere/👉Repo https://lnkd.in/ddQz9eps

🏓LATTE-MV: #3D Table Tennis🏓👉UC Berkeley unveils at #CVPR2025 a novel system for reconstructing monocular video of table tennis in 3D with uncertainty-aware controller that anticipates opponent actions. Code & Dataset announced, to be released💙👉Review https://t.ly/qPMOU👉Paper arxiv.org/pdf/2503.20936👉Project sastry-group.github.io/LATTE-MV/👉Repo github.com/sastry-group/LATTE-MV

🔥 Dereflection Any Image 🔥👉SJTU & #Huawei unveils DAI, novel diffusion-based framework able to recover from a wide range of reflection types. One-step diffusion with deterministic outputs & fast inference. Inference, pretrained models & training released💙👉Review https://t.ly/PDA9K 👉Paper https://arxiv.org/pdf/2503.17347👉Project abuuu122.github.io/DAI.github.io/👉Repo github.com/Abuuu122/Dereflection-Any-Image

🙀3D MultiModal Memory🙀👉M3 is a novel framework by UCSD & #NVIDIA for rendering 3D scenes w/ RGB & foundation model embeddings. Rich spatial & semantic understanding via novel memory system designed to retain multimodal info through videos👉Review https://t.ly/OrXZO👉Paper arxiv.org/pdf/2503.16413👉Project https://lnkd.in/dXAZ97KH👉Repo https://lnkd.in/dWvunCET

🥎LLM Spatial Understanding🥎👉SpatialLM by Manycore: novel LLM designed to process 3D point cloud data and generate structured 3D scene understanding outputs. Code, model & data 💙👉Review https://t.ly/ejr1s👉Project manycore-research.github.io/SpatialLM/👉Code github.com/manycore-research/SpatialLM🤗Models https://huggingface.co/manycore-research

🧞 IMPOSSIBLE Videos 🧞👉IPV-Bench: counterfactual and anti-reality scenes impossible in real world. A novel challenge designed to evaluate and foster progress in video understanding and generation. Code & 🤗-Data 💙👉Review https://t.ly/D7jhm👉Paper arxiv.org/pdf/2503.14378👉Project showlab.github.io/Impossible-Videos/ 👉Repo github.com/showlab/Impossible-Videos

🦎 Scaling Vision to 4K🦎👉PS3 by #Nvidia (+UC Berkeley) to scale-up CLIP-style vision pre-training to 4K with *near-constant* cost. Encoding LR global image and selectively processes only informative HR regions. Impressive work. Code/weights & 🤗 announced💙👉Review https://t.ly/WN479👉Paper https://lnkd.in/ddWq8UpX👉Project https://lnkd.in/dMkTY8-k👉Repo https://lnkd.in/d9YSB6yv

🌱 #Py4AI: line-up is official 🌱👉Last week we announced the first part of our incredible line-up for PY4AI 2025. It's time to disclose the second one and drive you crazy👇𝐓𝐡𝐞 𝐬𝐞𝐜𝐨𝐧𝐝 𝐛𝐚𝐭𝐜𝐡 𝐨𝐟 𝐬𝐩𝐞𝐚𝐤𝐞𝐫𝐬:🔥Alfredo Canziani | New York University🔥Fanny Bouton | OVHcloud🔥Full list: https://t.ly/JJP8B