🤖🧠 Concerto: How Joint 2D-3D Self-Supervised Learning Is Redefining Spatial Intelligence
🗓️ 09 Nov 2025
📚 AI News & Trends
The world of artificial intelligence is rapidly evolving and self-supervised learning has become a driving force behind breakthroughs in computer vision and 3D scene understanding. Traditional supervised learning relies heavily on labeled datasets which are expensive and time-consuming to produce. Self-supervised learning, on the other hand, extracts meaningful patterns without manual labels allowing models to ...
#SelfSupervisedLearning #ComputerVision #3DSceneUnderstanding #SpatialIntelligence #AIResearch #DeepLearning
🗓️ 09 Nov 2025
📚 AI News & Trends
The world of artificial intelligence is rapidly evolving and self-supervised learning has become a driving force behind breakthroughs in computer vision and 3D scene understanding. Traditional supervised learning relies heavily on labeled datasets which are expensive and time-consuming to produce. Self-supervised learning, on the other hand, extracts meaningful patterns without manual labels allowing models to ...
#SelfSupervisedLearning #ComputerVision #3DSceneUnderstanding #SpatialIntelligence #AIResearch #DeepLearning
✨Scaling Spatial Intelligence with Multimodal Foundation Models
📝 Summary:
SenseNova-SI is a new scaled multimodal foundation model that achieves superior spatial intelligence. By using 8 million diverse data samples, it sets unprecedented performance on various spatial benchmarks. The models are publicly released to foster further research.
🔹 Publication Date: Published on Nov 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.13719
• PDF: https://arxiv.org/pdf/2511.13719
• Project Page: https://huggingface.co/sensenova/SenseNova-SI-1.1-InternVL3-8B
• Github: https://github.com/OpenSenseNova/SenseNova-SI
🔹 Models citing this paper:
• https://huggingface.co/sensenova/SenseNova-SI-InternVL3-8B
• https://huggingface.co/sensenova/SenseNova-SI-InternVL3-2B
• https://huggingface.co/sensenova/SenseNova-SI-1.1-InternVL3-2B
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MultimodalAI #FoundationModels #SpatialIntelligence #ComputerVision #AI
📝 Summary:
SenseNova-SI is a new scaled multimodal foundation model that achieves superior spatial intelligence. By using 8 million diverse data samples, it sets unprecedented performance on various spatial benchmarks. The models are publicly released to foster further research.
🔹 Publication Date: Published on Nov 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.13719
• PDF: https://arxiv.org/pdf/2511.13719
• Project Page: https://huggingface.co/sensenova/SenseNova-SI-1.1-InternVL3-8B
• Github: https://github.com/OpenSenseNova/SenseNova-SI
🔹 Models citing this paper:
• https://huggingface.co/sensenova/SenseNova-SI-InternVL3-8B
• https://huggingface.co/sensenova/SenseNova-SI-InternVL3-2B
• https://huggingface.co/sensenova/SenseNova-SI-1.1-InternVL3-2B
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MultimodalAI #FoundationModels #SpatialIntelligence #ComputerVision #AI
arXiv.org
Scaling Spatial Intelligence with Multimodal Foundation Models
Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation models to...
✨COOPER: A Unified Model for Cooperative Perception and Reasoning in Spatial Intelligence
📝 Summary:
COOPER is a unified MLLM that integrates depth and segmentation modalities to enhance spatial intelligence. It uses adaptive interleaved reasoning, improving spatial reasoning by 6.91%. Learning to generate auxiliary modalities also strengthens spatial understanding, boosting distance and size es...
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04563
• PDF: https://arxiv.org/pdf/2512.04563
• Github: https://github.com/zhangzef/COOPER
🔹 Models citing this paper:
• https://huggingface.co/Starrrrrry/COOPER-AMG
• https://huggingface.co/Starrrrrry/COOPER
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Starrrrrry/COOPER_Train_Set
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MLLM #SpatialIntelligence #ComputerVision #AI #DeepLearning
📝 Summary:
COOPER is a unified MLLM that integrates depth and segmentation modalities to enhance spatial intelligence. It uses adaptive interleaved reasoning, improving spatial reasoning by 6.91%. Learning to generate auxiliary modalities also strengthens spatial understanding, boosting distance and size es...
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04563
• PDF: https://arxiv.org/pdf/2512.04563
• Github: https://github.com/zhangzef/COOPER
🔹 Models citing this paper:
• https://huggingface.co/Starrrrrry/COOPER-AMG
• https://huggingface.co/Starrrrrry/COOPER
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Starrrrrry/COOPER_Train_Set
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MLLM #SpatialIntelligence #ComputerVision #AI #DeepLearning