DCVSMNet: Double Cost Volume Stereo Matching Network

🖥 Github: https://github.com/m2219/dcvsmnet

⚙️ Paper: https://arxiv.org/pdf/2402.16473v1.pdf

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

⭐️ Tasks: https://paperswithcode.com/task/stereo-matching-1

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⏺ZHEM: An Integrated Data Processing Framework for Pretraining Foundation Models

🖥 Github: https://github.com/emanual20/zhem

💤 Paper: https://arxiv.org/pdf/2402.16358v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/wikitext-2

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📚 NATURAL LANGUAGE PROCESSING (2023)

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​​🧐 FIND: Interface Foundation Models' Embeddings

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🆗 Demo: http://find.xyzou.net

💐 ArXiv: https://arxiv.org/pdf/2312.07532.pdf

Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

⌨️ Github: https://github.com/naver/poc

🔖 Paper: https://arxiv.org/pdf/2402.16392v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/cityscapes

💫 Tasks: https://paperswithcode.com/task/segmentation

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🔥SOTA: Stable Diffusion 3: out ! 🔥

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✅ Largest models are superior to open SOTA models such as SDXL

🤥 Blog : https://stability.ai/news/stable-diffusion-3-research-paper

✅️ Paper : https://stabilityai-public-packages.s3.us-west-2.amazonaws.com/Stable+Diffusion+3+Paper.pdf

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RENT (Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning, ICLR 2024)

🖥 Github: https://github.com/BaeHeeSun/RENT

🔖 Paper: https://arxiv.org/pdf/2403.02690v1.pdf

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

✨ Tasks: https://paperswithcode.com/task/learning-with-noisy-labels

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🖼️ Differential Diffusion: Giving Each Pixel Its Strength 🔥

✅ code: github.com/exx8/differential-diffusion

✅ page: differential-diffusion.github.io

✅ paper: arxiv.org/abs/2306.00950

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💡 ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models

New framework designed for diffusion models (eg SD) to create images at any resolution and aspect ratio.
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💥 page : https://res-adapter.github.io

🫧 paper : https://arxiv.org/abs/2403.02084

⭐️ code : https://github.com/bytedance/res-adapter

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📁Machine Learning Techniques Applied to the Study of Drug Transporters

📕 Journal: Molecules (I.F.= 4.6)
📅 Publish year: 2023

🧑‍💻 Authors: Xiaorui Kong, Kexin Lin,Gaolei Wu
🤖 University: Department of Pharmacy, Dalian Medical University, China

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Recall-Oriented-CL-Framework

⌨️ Github: https://github.com/bigdata-inha/recall-oriented-cl-framework

📕 Paper: https://arxiv.org/pdf/2403.03082v1.pdf

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

✨ Tasks: https://paperswithcode.com/task/continual-learning

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🏎 TripoSR: Fast 3D Object Reconstruction from a Single Image

A state-of-the-art open source model for fast 3D reconstruction from a single image.

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🟢 paper : https://drive.google.com/file/d/1LWlZPT2aASi9jHiGVhDSr4YCTANoFW5t/view

🟢 code : https://github.com/VAST-AI-Research/TripoSR

🫥 Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models

📕 Journal: International Journal of Molecular Sciences (I.F.= 5.6)
📅 Publish year: 2023

🧑‍💻 Authors: Tianwei Yue,Yuanxin Wang,Longxiang Zhang, ...
🟢 University: Carnegie Mellon University, & Johns Hopkins University, & Michigan State University, USA

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📃 A Guide for the Bioinformatic Analysis of Metabolomics Data

🗓 Publish year: 2024

🧑‍💻Authors: Guillem Santamaria and Francisco R Pinto
⭐️ University: University of Lisbon, Portugal

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VTG-GPT

🖥 Github: https://github.com/YoucanBaby/VTG-GPT

📕 Paper: https://arxiv.org/pdf/2403.02076v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/activitynet-captions

✨ Tasks: https://paperswithcode.com/task/zero-shot-moment-retrieval

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☄️ Trends in using deep learning algorithms in biomedical prediction systems

➡️ Journal: Frontiers in Neuroscience (I.F.= 4.3)
🗓 Publish year: 2023

🧑‍💻 Authors: Yanbu Wang, Linqing Liu, Chao Wang
👀 University: Beijing Sport University-Peking University, Beijing, China

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Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning

🖥 Github: https://github.com/hikvision-research/3dvision

📕 Paper: https://arxiv.org/abs/2403.05117v1

🔥 Dataset: https://paperswithcode.com/dataset/scanobjectnn

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