Artificial Intelligence – Telegram
Artificial Intelligence
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Artificial Intelligence

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🖥 CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning

A novel method, CANIFE, that uses canaries - carefully crafted samples by a strong adversary to evaluate the empirical privacy of a training round.

conda create -n "canife" python=3.9
conda activate canife
pip install -r ./requirements.txt


⚙️Github: https://github.com/facebookresearch/canife

📄Paper: https://arxiv.org/abs/2210.02912v1

🗒Dataset: https://paperswithcode.com/dataset/cifar-10

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👣 OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds

⚙️Github: https://github.com/vlar-group/ogc

📄Paper: https://arxiv.org/abs/2210.04458v1

↪️ Demo: https://www.youtube.com/watch?v=dZBjvKWJ4K0

🗒Dataset: https://paperswithcode.com/dataset/kitti

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🛠 Understanding Embodied Reference with Touch-Line Transformer

conda create --name nvvc python=3.8
conda activate nvvc
pip install -r requirements.txt
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch


⚙️Github: https://github.com/yang-li-2000/understanding-embodied-reference-with-touch-line-transformer

📄Paper: https://arxiv.org/abs/2210.05668v2

🗒Dataset: https://paperswithcode.com/dataset/refcoco

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🗄 SUPERB-prosody: On The Utility of Self-supervised Models for Prosody-related Tasks

⚙️Github: https://github.com/jsalt-2022-ssl/superb-prosody

📄Paper: https://arxiv.org/abs/2210.07185v1

🗒Tasks: https://paperswithcode.com/task/prosody-prediction

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🔩 SubeventWriter: Iterative Sub-event Sequence Generation with Coherence Controller

⚙️Github: https://github.com/hkust-knowcomp/subeventwriter

📄Paper: https://arxiv.org/abs/2210.06694v1

🗒Dataset: https://paperswithcode.com/dataset/wikihow

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🖥 RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extraction

⚙️Github: https://github.com/m3dv/ribseg

📄Paper: https://arxiv.org/abs/2210.09309v1

🗒Dataset: https://doi.org/10.5281/zenodo.5336592

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🖥 HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks (NeurIPS 2022)

🖥 Github: https://github.com/macderru/hyperdomainnet

📄Paper: https://arxiv.org/abs/2210.08884v2

🔩 Colab: https://colab.research.google.com/drive/1QMylWjzPxvHtxm74U4lWRQXwquw5AaFL#scrollTo=si2tLKYLT-kV

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↪️ Targeted Adversarial Self-Supervised Learning

🖥 Github: https://github.com/Kim-Minseon/RoCL

📄Paper: https://arxiv.org/abs/2210.10482v1

🔩 Adversarial Self-Supervised Contrastive Learning: https://sites.google.com/view/rocl2020

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⭐️ Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions

🖥 Github: https://github.com/sinzlab/cgnf

➡️ Model: https://github.com/sinzlab/propose/tree/0.2.0/propose/models/flows

📄Paper: https://arxiv.org/abs/2210.11179v1

🔩 Dataset: https://paperswithcode.com/dataset/human3-6m

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🖥 TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation

🖥 Github: https://github.com/air-discover/toist

📄Paper: https://arxiv.org/abs/2210.10775v1

🔩 Dataset: https://github.com/coco-tasks/dataset

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Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report

🖥 Github: https://github.com/mv-lab/AISP

📄Paper: https://arxiv.org/abs/2210.11153v1

🔩 Starter guide: https://github.com/mv-lab/AISP/blob/main/aim22-reverseisp/official-starter-code.ipynb

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🖥 NVIDIA Federated Learning Application Runtime Environment

NVIDIA FLARE enables researchers to collaborate and build AI models without sharing private data.

pip install nvflare

🖥 Github: https://github.com/nvidia/nvflare

📄Paper: https://arxiv.org/abs/2210.13291v1

🔩 Starter guide: https://nvflare.readthedocs.io/en/main/getting_started.html

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🖥 Evaluating Long-Term Memory in 3D Mazes

pip install memory-maze

🖥 Github: https://github.com/jurgisp/memory-maze

📄Paper: https://arxiv.org/abs/2210.13383v1

🔩 Starter guide: https://www.dropbox.com/sh/c38sc5h7ltgyyzc/AAARVeKgnyaoBLGdYYVABh_Ja

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⭐️DiffusionDB

DiffusionDB is the first large-scale text-to-image prompt dataset.

🖥 Github: https://github.com/poloclub/diffusiondb

🗒 Paper: https://arxiv.org/abs/2210.14896v1

➡️ Dataset: https://huggingface.co/datasets/poloclub/diffusiondb

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