Artificial Intelligence l l AI Updates
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News about AI & DL & ML!!! Admin: @Gayrat_Tangriberganov
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❇️ Self-supervised Amodal Video Object Segmentation
#ObjectSegmentation
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❇️ Assignment-Space-Based Multi-Object Tracking and Segmentation
#ObjectTracking #Segmentation
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❇️ Context-Aware Relative Object Queries to Unify Video Instance and Panoptic Segmentation
#VideoSegmentation # InstanceSegmentation #PanopticSegmentation
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❇️ Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
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❇️ Expanding the Horizon for Surround-view 3D Object Detection
#ObjectDetection
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❇️ Semantic Line Combination Detection
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❇️ Recursive Video Lane Detection
#LaneDetection
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❇️ MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
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❇️ Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control
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❇️ MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
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❇️ ⚽️ COMPUTER VISION & SPORT ⚽️
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❇️ TACO: (Topics in Algorithmic COde generation dataset)
💥 Larger scale: TACO includes a training set (25,443 problems) and a test set (1,000 problems), making it the largest code generation dataset currently available.
💥 Higher quality: Each problem in the TACO dataset is designed to match a diverse set of solution answers, with answer sizes of up to 1.55M. This ensures that the model is not prone to overfitting during training and validates the effectiveness of evaluation results.
💥 Fine-grained labels: Each problem in the TACO dataset includes fine-grained labels such as task topics, algorithms, skills, and difficulty levels. These labels provide more accurate references for the training and evaluation of code generation models.
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❇️ R2E: Turning any GITHUB Repository into a
Programming Agent Environment
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❇️ Video Loopback for WebUI
#webui #LoRA
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❇️ ort is an (unofficial) ONNX Runtime 1.17 wrapper for Rust based on the now inactive onnxruntime-rs. ONNX Runtime accelerates ML inference on both CPU & GPU.
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❇️ Anyline: A Fast, Accurate, and Detailed Line Detection Preprocessor
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❇️ ViViD: Video Virtual Try-on using Diffusion Models
#Diffusion
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❇️ A Native-PyTorch Library for LLM Fine-tuning
#LLMs #FineTuning
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❇️ The Platonic Representation Hypothesis
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❇️ ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning
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