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Highlighted at CVPR 2025: Google DeepMind’s ‘Motion Prompting’ Paper Unlocks Granular Video Control

AI NewsJuly 7, 202531Views0Likes0Comments
Key Takeaways: Researchers from Google DeepMind, the University of Michigan & Brown university have developed “Motion Prompting,” a new method for controlling video generation using specific motion trajectories. The technique uses “motion prompts,” a flexible representation of movement that can be either sparse or dense, to guide a pre-trained video diffusion model. A key innovation…

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Gemini 2.5 model family expands

OpenAIJuly 7, 202527Views0Likes0Comments
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EmbodiedGen: A Scalable 3D World Generator for Realistic Embodied AI Simulations

RoboticsJuly 7, 202531Views0Likes0Comments
The Challenge of Scaling 3D Environments in Embodied AI Creating realistic and accurately scaled 3D environments is essential for training and evaluating embodied AI. However, current methods still rely on manually designed 3D graphics, which are costly and lack realism, thereby limiting scalability and generalization. Unlike internet-scale data used in models like GPT and CLIP,…

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BAAI Launches OmniGen2: A Unified Diffusion and Transformer Model for Multimodal AI

AI NewsJuly 2, 202529Views0Likes0Comments
Beijing Academy of Artificial Intelligence (BAAI) introduces OmniGen2, a next-generation, open-source multimodal generative model. Expanding on its predecessor OmniGen, the new architecture unifies text-to-image generation, image editing, and subject-driven generation within a single transformer framework. It innovates by decoupling the modeling of text and image generation, incorporating a reflective training mechanism, and implementing a purpose-built…

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UC San Diego Researchers Introduced Dex1B: A Billion-Scale Dataset for Dexterous Hand Manipulation in Robotics

RoboticsJuly 2, 202531Views0Likes0Comments
Challenges in Dexterous Hand Manipulation Data Collection Creating large-scale data for dexterous hand manipulation remains a major challenge in robotics. Although hands offer greater flexibility and richer manipulation potential than simpler tools, such as grippers, their complexity makes them difficult to control effectively. Many in the field have questioned whether dexterous hands are worth the…

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ByteDance Researchers Introduce VGR: A Novel Reasoning Multimodal Large Language Model (MLLM) with Enhanced Fine-Grained Visual Perception Capabilities

AI NewsJune 27, 202538Views0Likes0Comments
Why Multimodal Reasoning Matters for Vision-Language Tasks Multimodal reasoning enables models to make informed decisions and answer questions by combining both visual and textual information. This type of reasoning plays a central role in interpreting charts, answering image-based questions, and understanding complex visual documents. The goal is to make machines capable of using vision as…

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