AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates on Deep Learning, Machine Learning, and Computer Vision (with Papers).

Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/
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šŸ”„CutLER: Unsupervised Segmentation šŸ”„

šŸ‘‰Novel paper by #META on detection & instance segmentation without human annotations

šŸ˜ŽReview https://bit.ly/3DlFiUG
šŸ˜ŽPaper arxiv.org/pdf/2301.11320.pdf
šŸ˜ŽCode github.com/facebookresearch/CutLER
šŸ˜ŽProject people.eecs.berkeley.edu/~xdwang/projects/CutLER
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šŸ˜ CLIP/GPT3-driven Affective Faces šŸ˜

šŸ‘‰Columbia unveils a neural framework for facial expressions retrieval given the context of the speaker

šŸ˜ŽReview https://bit.ly/3HERna0
šŸ˜ŽPaper arxiv.org/pdf/2301.10939.pdf
šŸ˜ŽProject realtalk.cs.columbia.edu
šŸ˜ŽCode github.com/scottgeng00/realtalk
šŸ”„12ā¤5šŸ‘1🄰1🤩1
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🐦 Physics-inspired Computer Vision 🐦

šŸ‘‰UCLA unveils PhyCV, the first Physics-inspired Computer Vision Library

šŸ˜ŽReview https://bit.ly/3HEWozI
šŸ˜ŽCode github.com/JalaliLabUCLA/phycv
šŸ˜ŽProject photonics.ucla.edu/2022/05/12/jalali-lab-open-sources-phycv-a-physics-inspired-computer-vision-library/
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šŸŽ·Audio-Visual Semantic SegmentationšŸŽ·

šŸ‘‰A novel problem in #AI: pixel-level segmentation of objects that produce sound in the image frame

šŸ˜ŽReview https://bit.ly/3wFY6dw
šŸ˜ŽPaper arxiv.org/pdf/2301.13190.pdf
šŸ˜ŽProject opennlplab.github.io/AVSBench
šŸ˜ŽCode github.com/OpenNLPLab/AVSBench
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šŸš› Text-driven Video Neural Editing šŸš›

šŸ‘‰A novel text-guided video editing with both appearance/shape

šŸ˜ŽReview https://bit.ly/3YcfMJO
šŸ˜ŽPaper arxiv.org/pdf/2301.13173.pdf
šŸ˜ŽProject text-video-edit.github.io/
šŸ”„12šŸ‘1
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⭐ Mono-STAR: Unified Track/3D ⭐

šŸ‘‰Real-time 3D unified framework for semantic fusion, tracking, non-rigid deformation, and topological changes

šŸ˜ŽReview https://bit.ly/3Dxvxmx
šŸ˜ŽPaper arxiv.org/pdf/2301.13244.pdf
šŸ˜ŽProject github.com/changhaonan/Mono-STAR-demo
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šŸ›‹ļøšŸ›‹ļø 100% Accurated #3D Labeling šŸ›‹ļøšŸ›‹ļø

šŸ‘‰#Amazon unveils a novel tool for fine-grained 3D part labeling. Up to 100% accuracy! Paper only😢

šŸ˜ŽReview https://bit.ly/3kYpQHQ
šŸ˜ŽPaper https://arxiv.org/pdf/2301.10460.pdf
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šŸ’§FLOW360: 360° Neural Optical FlowšŸ’§

šŸ‘‰ The first perceptually realistic 360° video benchmark dataset + SLOF method for OF tracking

šŸ˜ŽReview https://bit.ly/3wMZZoX
šŸ˜ŽPaper arxiv.org/pdf/2301.11880.pdf
šŸ˜ŽProject https://siamlof.github.io
šŸ‘7🤯2šŸ”„1
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šŸ“DREAMIX:General Diffusive Video EditoršŸ“

šŸ‘‰#Google unveils the first diffusion-based method able to perform text-based motion/appearance editing of general videos

šŸ˜ŽReview https://bit.ly/3I3Hq6B
šŸ˜ŽPaper arxiv.org/pdf/2302.01329.pdf
šŸ˜ŽProject dreamix-video-editing.github.io/
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🧩 Text-Guided #3D Texturing 🧩

šŸ‘‰ Text-Guided HQ textures via iterative diffusion-based process

šŸ˜ŽReview https://bit.ly/3ldC6Ez
šŸ˜ŽProject texturepaper.github.io/TEXTurePaper
šŸ˜ŽCode github.com/TEXTurePaper/TEXTurePaper
šŸ˜ŽPaper texturepaper.github.io/TEXTurePaper/static/paper.pdf
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🦚 MOSE: coMplex video Object SEgmentation 🦚

šŸ‘‰Novel Dataset for VOS is out! SOTA method on DAVIS is only 59.4% on MOSE

šŸ˜ŽReview https://bit.ly/40yzSzW
šŸ˜ŽPaper arxiv.org/pdf/2302.01872.pdf
šŸ˜ŽProject henghuiding.github.io/MOSE/
šŸ˜ŽCode github.com/henghuiding/MOSE-api
ā¤7šŸ‘2šŸ”„2
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🌘 Gen-1: next-gen Generative #AI 🌘

šŸ‘‰#Runway unveils Gen-1: the next step forward for Generative AI. Registration available for beta -> hurry up!

šŸ˜ŽReview https://bit.ly/3YqQYh8
šŸ˜ŽPaper arxiv.org/pdf/2302.03011.pdf
šŸ˜ŽProject https://research.runwayml.com/gen1
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šŸ—æDirectMHP: Multi-Head Pose EstimationšŸ—æ

šŸ‘‰Novel E2E multi-person head pose estimation (MPHPE) under full-range angles

šŸ˜ŽReview https://bit.ly/3HJubXg
šŸ˜ŽPaper arxiv.org/pdf/2302.01110.pdf
šŸ˜ŽCode github.com/hnuzhy/DirectMHP
šŸ”„13šŸ‘1
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🧱 LEGO-Net: Objects in Rooms 🧱

šŸ‘‰Transformer-based iterative method for rearrangement of objects in messy rooms

šŸ˜ŽReview https://bit.ly/3HR0fs6
šŸ˜ŽPaper arxiv.org/pdf/2301.09629.pdf
šŸ˜ŽProject ivl.cs.brown.edu/#/projects/lego-net
šŸ”„11🤯4
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šŸŽƒ In-N-Out: 3D-aware OOD video editing šŸŽƒ

šŸ‘‰Novel 3D-aware video editing able to manipulate OOD objects (e.g. heavy makeup, accessories)

šŸ˜ŽReview https://bit.ly/3jN0CMu
šŸ˜ŽPaper arxiv.org/pdf/2302.04871.pdf
šŸ˜ŽProject https://in-n-out-3d.github.io
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🄸 MEGANE: Generative Morphable Eyeglass 🄸

šŸ‘‰#META unveils the most advanced #3D compositional morphable AI for eyeglasses (HD geometry/photometric interaction)

šŸ˜ŽReview https://bit.ly/3jOWifu
šŸ˜ŽPaper arxiv.org/pdf/2302.04868.pdf
šŸ˜ŽProject junxuan-li.github.io/megane
šŸ”„9🤯3šŸ‘2🤩1
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šŸ’˜ 3D-aware Blending with NeRF šŸ’˜

šŸ‘‰Novel 3D-aware blending method via generative NeRFs

šŸ˜ŽReview https://bit.ly/3lBEJA2
šŸ˜ŽPaper arxiv.org/pdf/2302.06608.pdf
šŸ˜ŽProject blandocs.github.io/blendnerf
šŸ˜ŽCode github.com/naver-ai/BlendNeRF
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šŸŒ… Semantics-guided natural synthesis šŸŒ…

šŸ‘‰Alibaba #AI unveils a novel semantics-guided synthesis of natural scenes

šŸ˜ŽReview https://bit.ly/4115MVJ
šŸ˜ŽPaper arxiv.org/pdf/2302.07224.pdf
šŸ˜ŽProject zju3dv.github.io/paintingnature
šŸ‘5šŸ”„1🤯1
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šŸ¦ž SOTA ALERT: YOWOv2 is out! šŸ¦ž

šŸ‘‰ The 2nd-gen of YOWO, real-time detection of spatio-temporal actions

šŸ˜ŽReview https://bit.ly/3IscY60
šŸ˜ŽPaper arxiv.org/pdf/2302.06848v1.pdf
šŸ˜ŽCode github.com/yjh0410/YOWOv2
šŸ”„17šŸ‘2
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šŸ“¬ DIVOTrack: crossview MOT dataset šŸ“¬

šŸ‘‰ DIVOTrack + CrossMOT: the ultimate solution for MOT in realistic scenario

šŸ˜ŽReview https://bit.ly/3YSFZgL
šŸ˜ŽPaper arxiv.org/pdf/2302.07676.pdf
šŸ˜ŽCode github.com/shengyuhao/DIVOTrack
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