🚀 Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset
🖥 Github: https://github.com/liamlian0727/usis10k
📕 Paper: https://arxiv.org/abs/2406.06039v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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TSI-Bench: Benchmarking Time Series Imputation
🖥 Github: https://github.com/WenjieDu/Awesome_Imputation
📕 Paper: https://arxiv.org/pdf/2406.12747v1.pdf
🔥Dataset: https://github.com/WenjieDu/TSDB
@ArtificialIntelligencedl
🔥Dataset: https://github.com/WenjieDu/TSDB
@ArtificialIntelligencedl
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Consistency Models Made Easy
🖥 Github: https://github.com/locuslab/ect
📕 Paper: https://arxiv.org/abs/2406.14548v1
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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LangSuitE: Planning, Controlling and Interacting with Large Language Models in Embodied Text Environments
🖥 Github: https://github.com/bigai-nlco/langsuite
📕 Paper: https://arxiv.org/abs/2406.16294v1
🔥Dataset: https://paperswithcode.com/dataset/ai2-thor
@ArtificialIntelligencedl
🔥Dataset: https://paperswithcode.com/dataset/ai2-thor
@ArtificialIntelligencedl
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Point-SAM: Promptable 3D Segmentation Model for Point Clouds
🖥 Github: https://github.com/zyc00/point-sam
📕 Paper: https://arxiv.org/abs/2406.17741v1
🔥Dataset: https://paperswithcode.com/dataset/shapenet
@ArtificialIntelligencedl
🔥Dataset: https://paperswithcode.com/dataset/shapenet
@ArtificialIntelligencedl
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🏥 MedMNIST-C: benchmark dataset based on the MedMNIST+ collection covering 12 2D datasets and 9 imaging modalities.
🖥 Github: https://github.com/francescodisalvo05/medmnistc-api
📕 Paper: https://arxiv.org/abs/2406.17536v2
🔥Dataset: https://paperswithcode.com/dataset/imagenet-c
@ArtificialIntelligencedl
pip install medmnistc
🔥Dataset: https://paperswithcode.com/dataset/imagenet-c
@ArtificialIntelligencedl
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New open model alert by Shanghai AI Laboratory 🚨
Welcome Internal 2.5
🔥Very high quality 7B model
🚀Up to 1 million context window
🔧Tool usage capabilities
Looking forward to playing with it
https://huggingface.co/collections/internlm/internlm25-66853f32717072d17581bc13
@ArtificialIntelligencedl
Welcome Internal 2.5
🔥Very high quality 7B model
🚀Up to 1 million context window
🔧Tool usage capabilities
Looking forward to playing with it
https://huggingface.co/collections/internlm/internlm25-66853f32717072d17581bc13
@ArtificialIntelligencedl
⚡️Лучший способ получать свежие обновления и следить за трендами в разработке на вашем языке. Находите свой стек и подписывайтесь:
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📕Ит-книги бесплатно: https://www.group-telegram.com/addlist/BkskQciUW_FhNjEy
Seq2Seq: Sequence-to-Sequence Generator
🖥 Github: https://github.com/fiy2w/mri_seq2seq
📕 Paper: https://arxiv.org/abs/2407.02911v1
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@ArtificialIntelligencedl
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@ArtificialIntelligencedl
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Minutes to Seconds: Speeded-up DDPM-based Image Inpainting with Coarse-to-Fine Sampling
🖥 Github: https://github.com/linghuyuhangyuan/m2s
📕 Paper: https://arxiv.org/abs/2407.05875v1
🔥Dataset: https://paperswithcode.com/task/denoising
🔥Dataset: https://paperswithcode.com/task/denoising
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Unified Embedding Alignment for Open-Vocabulary Video Instance Segmentation (ECCV 2024)
🖥 Github: https://github.com/fanghaook/ovformer
📕 Paper: https://arxiv.org/abs/2407.07427v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Multimodal contrastive learning for spatial gene expression prediction using histology images
🖥 Github: https://github.com/shizhiceng/mclstexp
📕 Paper: https://arxiv.org/abs/2407.08216v1
🔥Dataset: https://doi.org/10.48610/4fb74a9.
@ArtificialIntelligencedl
🔥Dataset: https://doi.org/10.48610/4fb74a9.
@ArtificialIntelligencedl
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Multimodal contrastive learning for spatial gene expression prediction using histology images
🖥 Github: https://github.com/modelscope/data-juicer
📕 Paper: https://arxiv.org/abs/2407.08583v1
🚀 Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
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🌟 Gradient Boosting Reinforcement Learning (GBRL)
🖥 Github: https://github.com/nvlabs/gbrl
📕 Paper: https://arxiv.org/abs/2407.08250v1
🚀 Dataset: https://paperswithcode.com/task/reinforcement-learning-2
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/task/reinforcement-learning-2
@ArtificialIntelligencedl
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🌟 An Empirical Study of Mamba-based Pedestrian Attribute Recognition
🖥 Github: https://github.com/event-ahu/openpar
📕 Paper: https://arxiv.org/pdf/2407.10374v1.pdf
🚀 Dataset: https://paperswithcode.com/dataset/peta
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/peta
@ArtificialIntelligencedl
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Aligning Sight and Sound: Advanced Sound Source Localization Through Audio-Visual Alignment
🖥 Github: https://github.com/kaistmm/SSLalignment
📕 Paper: https://arxiv.org/abs/2407.13676v1
🚀 Dataset: https://paperswithcode.com/dataset/is3-interactive-synthetic-sound-source
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/is3-interactive-synthetic-sound-source
@ArtificialIntelligencedl
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🚀 Dataset: https://paperswithcode.com/dataset/behave
@ArtificialIntelligencedl
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⚡️ EMO-Disentanger
🖥 Github: https://github.com/yuer867/emo-disentanger
📕 Paper: https://arxiv.org/abs/2407.20955v1
🚀 Dataset: https://paperswithcode.com/dataset/emopia
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/emopia
@ArtificialIntelligencedl
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No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
🖥 Github: https://github.com/themody/no-learning-rates-needed-introducing-salsa-stable-armijo-line-search-adaptation
📕 Paper: https://arxiv.org/abs/2407.20650v1
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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