✨EtCon: Edit-then-Consolidate for Reliable Knowledge Editing
📝 Summary:
A novel knowledge editing framework, Edit-then-Consolidate, addresses overfitting and lack of knowledge integration in large language models through targeted fine-tuning and policy optimization, enhan...
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04753
• PDF: https://arxiv.org/pdf/2512.04753
• Github: https://github.com/RlinL/EtCon
==================================
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📝 Summary:
A novel knowledge editing framework, Edit-then-Consolidate, addresses overfitting and lack of knowledge integration in large language models through targeted fine-tuning and policy optimization, enhan...
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04753
• PDF: https://arxiv.org/pdf/2512.04753
• Github: https://github.com/RlinL/EtCon
==================================
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✨Beyond Unified Models: A Service-Oriented Approach to Low Latency, Context Aware Phonemization for Real Time TTS
📝 Summary:
A framework is proposed to improve phonemization quality in TTS systems without sacrificing real-time performance through lightweight context-aware phonemization and a service-oriented architecture. A...
🔹 Publication Date: Published on Dec 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08006
• PDF: https://arxiv.org/pdf/2512.08006
• Github: https://github.com/MahtaFetrat/Piper-with-LCA-Phonemizer
==================================
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📝 Summary:
A framework is proposed to improve phonemization quality in TTS systems without sacrificing real-time performance through lightweight context-aware phonemization and a service-oriented architecture. A...
🔹 Publication Date: Published on Dec 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08006
• PDF: https://arxiv.org/pdf/2512.08006
• Github: https://github.com/MahtaFetrat/Piper-with-LCA-Phonemizer
==================================
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❤1
✨Composing Concepts from Images and Videos via Concept-prompt Binding
📝 Summary:
Bind & Compose introduces a one-shot method for composing visual concepts from images and videos. It binds concepts to prompt tokens using hierarchical binders and novel strategies, achieving superior consistency, fidelity, and motion quality.
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09824
• PDF: https://arxiv.org/pdf/2512.09824
• Project Page: https://refkxh.github.io/BiCo_Webpage/
• Github: https://github.com/refkxh/bico
==================================
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#AI #ComputerVision #GenerativeAI #VisualConcepts #PromptEngineering
📝 Summary:
Bind & Compose introduces a one-shot method for composing visual concepts from images and videos. It binds concepts to prompt tokens using hierarchical binders and novel strategies, achieving superior consistency, fidelity, and motion quality.
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09824
• PDF: https://arxiv.org/pdf/2512.09824
• Project Page: https://refkxh.github.io/BiCo_Webpage/
• Github: https://github.com/refkxh/bico
==================================
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✨TED-4DGS: Temporally Activated and Embedding-based Deformation for 4DGS Compression
📝 Summary:
TED-4DGS efficiently compresses dynamic 3D scenes using sparse anchor-based 3D Gaussian Splatting with novel temporal activation and embedding-based deformation. It optimizes rate-distortion with an implicit neural representation hyperprior and autoregressive model, achieving state-of-the-art com...
🔹 Publication Date: Published on Dec 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05446
• PDF: https://arxiv.org/pdf/2512.05446
==================================
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#4DGS #3DCompression #NeuralRendering #ComputerVision #DynamicScenes
📝 Summary:
TED-4DGS efficiently compresses dynamic 3D scenes using sparse anchor-based 3D Gaussian Splatting with novel temporal activation and embedding-based deformation. It optimizes rate-distortion with an implicit neural representation hyperprior and autoregressive model, achieving state-of-the-art com...
🔹 Publication Date: Published on Dec 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05446
• PDF: https://arxiv.org/pdf/2512.05446
==================================
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✨VideoSSM: Autoregressive Long Video Generation with Hybrid State-Space Memory
📝 Summary:
VideoSSM proposes a hybrid state-space memory model for long video generation. It unifies autoregressive diffusion with global state-space memory and local context to achieve state-of-the-art temporal consistency and motion stability. This enables scalable, interactive minute-scale video synthesis.
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04519
• PDF: https://arxiv.org/pdf/2512.04519
==================================
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#VideoGeneration #GenerativeAI #DiffusionModels #StateSpaceModels #DeepLearning
📝 Summary:
VideoSSM proposes a hybrid state-space memory model for long video generation. It unifies autoregressive diffusion with global state-space memory and local context to achieve state-of-the-art temporal consistency and motion stability. This enables scalable, interactive minute-scale video synthesis.
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04519
• PDF: https://arxiv.org/pdf/2512.04519
==================================
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✨BrainExplore: Large-Scale Discovery of Interpretable Visual Representations in the Human Brain
📝 Summary:
An automated framework identifies and explains visual representations in human brain fMRI data using unsupervised decomposition and natural language denoscriptions. This large-scale method reveals thousands of interpretable visual concepts, including previously unknown fine-grained representations ...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08560
• PDF: https://arxiv.org/pdf/2512.08560
• Project Page: https://navvewas.github.io/BrainExplore/
✨ Spaces citing this paper:
• https://huggingface.co/spaces/mcosarinsky/BrainExplore-demo
==================================
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#Neuroscience #BrainMapping #fMRI #AIResearch #DataScience
📝 Summary:
An automated framework identifies and explains visual representations in human brain fMRI data using unsupervised decomposition and natural language denoscriptions. This large-scale method reveals thousands of interpretable visual concepts, including previously unknown fine-grained representations ...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08560
• PDF: https://arxiv.org/pdf/2512.08560
• Project Page: https://navvewas.github.io/BrainExplore/
✨ Spaces citing this paper:
• https://huggingface.co/spaces/mcosarinsky/BrainExplore-demo
==================================
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❤1
✨IF-Bench: Benchmarking and Enhancing MLLMs for Infrared Images with Generative Visual Prompting
📝 Summary:
IF-Bench is introduced as the first benchmark to evaluate multimodal large language models on infrared images using diverse assessment strategies. It includes varied infrared images and question-answer pairs for systematic evaluation of over 40 models. The paper also proposes GenViP, a training-f...
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09663
• PDF: https://arxiv.org/pdf/2512.09663
🔹 Models citing this paper:
• https://huggingface.co/casiatao/Qwen-Edit-2509-FT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/casiatao/IF-Bench
==================================
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#MLLMs #InfraredImaging #Benchmarking #GenerativeAI #AIResearch
📝 Summary:
IF-Bench is introduced as the first benchmark to evaluate multimodal large language models on infrared images using diverse assessment strategies. It includes varied infrared images and question-answer pairs for systematic evaluation of over 40 models. The paper also proposes GenViP, a training-f...
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09663
• PDF: https://arxiv.org/pdf/2512.09663
🔹 Models citing this paper:
• https://huggingface.co/casiatao/Qwen-Edit-2509-FT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/casiatao/IF-Bench
==================================
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✨Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation
📝 Summary:
DualVLN is a dual-system model for vision-language navigation. It integrates a VLM global planner with a fast local policy for smooth actions, enabling robust real-time control and long-horizon planning in dynamic environments.
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08186
• PDF: https://arxiv.org/pdf/2512.08186
• Project Page: https://internrobotics.github.io/internvla-n1-dualvln.github.io/
• Github: https://github.com/InternRobotics/InternNav
🔹 Models citing this paper:
• https://huggingface.co/InternRobotics/InternVLA-N1-System2
• https://huggingface.co/InternRobotics/InternVLA-N1-w-NavDP
• https://huggingface.co/InternRobotics/InternVLA-N1-DualVLN
==================================
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📝 Summary:
DualVLN is a dual-system model for vision-language navigation. It integrates a VLM global planner with a fast local policy for smooth actions, enabling robust real-time control and long-horizon planning in dynamic environments.
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08186
• PDF: https://arxiv.org/pdf/2512.08186
• Project Page: https://internrobotics.github.io/internvla-n1-dualvln.github.io/
• Github: https://github.com/InternRobotics/InternNav
🔹 Models citing this paper:
• https://huggingface.co/InternRobotics/InternVLA-N1-System2
• https://huggingface.co/InternRobotics/InternVLA-N1-w-NavDP
• https://huggingface.co/InternRobotics/InternVLA-N1-DualVLN
==================================
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✨TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels
📝 Summary:
TrackingWorld provides dense 3D tracking of pixels in a world-centric coordinate system by upsampling sparse 2D tracks and optimizing camera poses and 3D coordinates. AI-generated summary Monocular 3D...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08358
• PDF: https://arxiv.org/pdf/2512.08358
• Project Page: https://igl-hkust.github.io/TrackingWorld.github.io/
==================================
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📝 Summary:
TrackingWorld provides dense 3D tracking of pixels in a world-centric coordinate system by upsampling sparse 2D tracks and optimizing camera poses and 3D coordinates. AI-generated summary Monocular 3D...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08358
• PDF: https://arxiv.org/pdf/2512.08358
• Project Page: https://igl-hkust.github.io/TrackingWorld.github.io/
==================================
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❤1
✨Rethinking Chain-of-Thought Reasoning for Videos
📝 Summary:
This paper demonstrates that concise chains of thought and reduced visual tokens efficiently enable video reasoning in MLLMs. Their framework improves inference speed and performance, proving long, human-like reasoning is not necessary for effective video understanding.
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09616
• PDF: https://arxiv.org/pdf/2512.09616
• Github: https://github.com/LaVi-Lab/Rethink_CoT_Video
==================================
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📝 Summary:
This paper demonstrates that concise chains of thought and reduced visual tokens efficiently enable video reasoning in MLLMs. Their framework improves inference speed and performance, proving long, human-like reasoning is not necessary for effective video understanding.
🔹 Publication Date: Published on Dec 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09616
• PDF: https://arxiv.org/pdf/2512.09616
• Github: https://github.com/LaVi-Lab/Rethink_CoT_Video
==================================
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❤1
✨Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction
📝 Summary:
MineROI-Net is a Transformer model predicting Bitcoin ASIC hardware profitability within one year, addressing acquisition timing. It achieves 83.7% accuracy, outperforming baselines, and precisely identifies profitable or unprofitable periods to reduce financial risk.
🔹 Publication Date: Published on Dec 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05402
• PDF: https://arxiv.org/pdf/2512.05402
==================================
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#DeepLearning #Bitcoin #CryptoMining #FinancialModeling #AIResearch
📝 Summary:
MineROI-Net is a Transformer model predicting Bitcoin ASIC hardware profitability within one year, addressing acquisition timing. It achieves 83.7% accuracy, outperforming baselines, and precisely identifies profitable or unprofitable periods to reduce financial risk.
🔹 Publication Date: Published on Dec 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05402
• PDF: https://arxiv.org/pdf/2512.05402
==================================
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❤1
✨GimbalDiffusion: Gravity-Aware Camera Control for Video Generation
📝 Summary:
GimbalDiffusion offers precise text-to-video camera control by using absolute, gravity-aligned coordinates. This framework defines interpretable camera trajectories, enhancing robustness and diverse motion beyond relative methods.
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09112
• PDF: https://arxiv.org/pdf/2512.09112
• Project Page: https://lvsn.github.io/GimbalDiffusion/
==================================
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📝 Summary:
GimbalDiffusion offers precise text-to-video camera control by using absolute, gravity-aligned coordinates. This framework defines interpretable camera trajectories, enhancing robustness and diverse motion beyond relative methods.
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09112
• PDF: https://arxiv.org/pdf/2512.09112
• Project Page: https://lvsn.github.io/GimbalDiffusion/
==================================
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✨Towards a Science of Scaling Agent Systems
📝 Summary:
A quantitative framework for agent system scaling using empirical coordination metrics identifies optimal multi-agent strategies based on task properties. AI-generated summary Agents, language model (...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08296
• PDF: https://arxiv.org/pdf/2512.08296
==================================
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📝 Summary:
A quantitative framework for agent system scaling using empirical coordination metrics identifies optimal multi-agent strategies based on task properties. AI-generated summary Agents, language model (...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08296
• PDF: https://arxiv.org/pdf/2512.08296
==================================
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❤1
🤖🧠 How to Run and Fine-Tune Kimi K2 Thinking Locally with Unsloth
🗓️ 11 Dec 2025
📚 AI News & Trends
The demand for efficient and powerful large language models (LLMs) continues to rise as developers and researchers seek new ways to optimize reasoning, coding, and conversational AI performance. One of the most impressive open-source AI systems available today is Kimi K2 Thinking, created by Moonshot AI. Through collaboration with Unsloth, users can now fine-tune and ...
#KimiK2Thinking #Unsloth #LLMs #LargeLanguageModels #AI #FineTuning
🗓️ 11 Dec 2025
📚 AI News & Trends
The demand for efficient and powerful large language models (LLMs) continues to rise as developers and researchers seek new ways to optimize reasoning, coding, and conversational AI performance. One of the most impressive open-source AI systems available today is Kimi K2 Thinking, created by Moonshot AI. Through collaboration with Unsloth, users can now fine-tune and ...
#KimiK2Thinking #Unsloth #LLMs #LargeLanguageModels #AI #FineTuning
❤1
✨The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality
📝 Summary:
The FACTS Leaderboard is a new comprehensive benchmark evaluating LLMs' factual accuracy. It uses four sub-leaderboards: image-based, closed-book, search-augmented, and document-grounded, to holistically assess factuality with automated judges.
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10791
• PDF: https://arxiv.org/pdf/2512.10791
• Project Page: https://www.kaggle.com/benchmarks/google/facts
==================================
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📝 Summary:
The FACTS Leaderboard is a new comprehensive benchmark evaluating LLMs' factual accuracy. It uses four sub-leaderboards: image-based, closed-book, search-augmented, and document-grounded, to holistically assess factuality with automated judges.
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10791
• PDF: https://arxiv.org/pdf/2512.10791
• Project Page: https://www.kaggle.com/benchmarks/google/facts
==================================
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✨Evaluating Gemini Robotics Policies in a Veo World Simulator
📝 Summary:
A generative evaluation system using a frontier video model (Veo) enables comprehensive policy evaluation in robotics, including nominal performance, out-of-distribution generalization, and safety che...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10675
• PDF: https://arxiv.org/pdf/2512.10675
==================================
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📝 Summary:
A generative evaluation system using a frontier video model (Veo) enables comprehensive policy evaluation in robotics, including nominal performance, out-of-distribution generalization, and safety che...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10675
• PDF: https://arxiv.org/pdf/2512.10675
==================================
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✨Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents
📝 Summary:
Fed-SE, a Federated Self-Evolution framework, enhances LLM agents in privacy-constrained environments by local parameter-efficient fine-tuning and global aggregation in a low-rank subspace. AI-generat...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08870
• PDF: https://arxiv.org/pdf/2512.08870
==================================
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📝 Summary:
Fed-SE, a Federated Self-Evolution framework, enhances LLM agents in privacy-constrained environments by local parameter-efficient fine-tuning and global aggregation in a low-rank subspace. AI-generat...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08870
• PDF: https://arxiv.org/pdf/2512.08870
==================================
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✨Are We Ready for RL in Text-to-3D Generation? A Progressive Investigation
📝 Summary:
This study systematically explores reinforcement learning for text-to-3D generation, addressing reward designs, RL algorithms, and introducing a new benchmark. It develops AR3D-R1, the first RL-enhanced text-to-3D model, demonstrating RLs effectiveness across 3D generation stages.
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10949
• PDF: https://arxiv.org/pdf/2512.10949
• Github: https://github.com/Ivan-Tang-3D/3DGen-R1
==================================
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📝 Summary:
This study systematically explores reinforcement learning for text-to-3D generation, addressing reward designs, RL algorithms, and introducing a new benchmark. It develops AR3D-R1, the first RL-enhanced text-to-3D model, demonstrating RLs effectiveness across 3D generation stages.
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10949
• PDF: https://arxiv.org/pdf/2512.10949
• Github: https://github.com/Ivan-Tang-3D/3DGen-R1
==================================
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✨OPV: Outcome-based Process Verifier for Efficient Long Chain-of-Thought Verification
📝 Summary:
The Outcome-based Process Verifier (OPV) improves the verification of complex reasoning chains in large language models by combining outcome-based and process-based verification with iterative active ...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10756
• PDF: https://arxiv.org/pdf/2512.10756
==================================
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📝 Summary:
The Outcome-based Process Verifier (OPV) improves the verification of complex reasoning chains in large language models by combining outcome-based and process-based verification with iterative active ...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10756
• PDF: https://arxiv.org/pdf/2512.10756
==================================
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✨MoCapAnything: Unified 3D Motion Capture for Arbitrary Skeletons from Monocular Videos
📝 Summary:
MoCapAnything is a reference-guided framework that reconstructs rotation-based animations from monocular video for arbitrary rigged 3D assets, enabling cross-species retargeting and scalable 3D motion...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10881
• PDF: https://arxiv.org/pdf/2512.10881
==================================
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📝 Summary:
MoCapAnything is a reference-guided framework that reconstructs rotation-based animations from monocular video for arbitrary rigged 3D assets, enabling cross-species retargeting and scalable 3D motion...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10881
• PDF: https://arxiv.org/pdf/2512.10881
==================================
For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research