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🦕 6D Non-Prehensile Manipulation 🦕
👉#META (+CMU) unveils HACMan, novel 6D non-prehensile manipulation of objects
😎Review https://bit.ly/3NP1jl1
😎Paper arxiv.org/pdf/2305.03942.pdf
😎Project hacman-2023.github.io
👉#META (+CMU) unveils HACMan, novel 6D non-prehensile manipulation of objects
😎Review https://bit.ly/3NP1jl1
😎Paper arxiv.org/pdf/2305.03942.pdf
😎Project hacman-2023.github.io
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🛸 Virtual Occlusions in #AR 🛸
👉Niantic (#pokemongo) on a novel approach for virtual assets to appear ‘sitting among’ the real world objects
😎Review https://bit.ly/3o04wn6
😎Paper arxiv.org/pdf/2305.07014.pdf
😎Project nianticlabs.github.io/implicit-depth
😎Code github.com/nianticlabs/implicit-depth
👉Niantic (#pokemongo) on a novel approach for virtual assets to appear ‘sitting among’ the real world objects
😎Review https://bit.ly/3o04wn6
😎Paper arxiv.org/pdf/2305.07014.pdf
😎Project nianticlabs.github.io/implicit-depth
😎Code github.com/nianticlabs/implicit-depth
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🍿 De-Aging Harrison Ford via SD 🍿
👉Stable Diffusion for Hollywood: preview of the next autotune of entertainment industry. A discussion👇
😎 More: https://bit.ly/41EzaQK
👉Stable Diffusion for Hollywood: preview of the next autotune of entertainment industry. A discussion👇
😎 More: https://bit.ly/41EzaQK
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🪰 #3D Auto-Reconstruction 🪰
👉AutoRecon: automated discovery & reconstruction of objects from multi-view pics.
😎Review https://bit.ly/3MxI0f4
😎Paper arxiv.org/pdf/2305.08810.pdf
😎Project zju3dv.github.io/autorecon/
😎Code github.com/zju3dv/AutoRecon
👉AutoRecon: automated discovery & reconstruction of objects from multi-view pics.
😎Review https://bit.ly/3MxI0f4
😎Paper arxiv.org/pdf/2305.08810.pdf
😎Project zju3dv.github.io/autorecon/
😎Code github.com/zju3dv/AutoRecon
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👚 Multi-Layered 3D Garments Animation 👚
👉S-Lab unveils LayersNet: animating multi-layered garments driven by various external forces, such as human bodies & wind
😎Review https://bit.ly/435b42F
😎Paper arxiv.org/pdf/2305.10418.pdf
😎Project mmlab-ntu.github.io/project/layersnet
👉S-Lab unveils LayersNet: animating multi-layered garments driven by various external forces, such as human bodies & wind
😎Review https://bit.ly/435b42F
😎Paper arxiv.org/pdf/2305.10418.pdf
😎Project mmlab-ntu.github.io/project/layersnet
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🎫 100% Mask-Free VIS 🎫
👉ETH Z unveils MaskFreeVIS: novel high-performing VIS without any mask annotations.
😎Review https://bit.ly/3Wg7CQB
😎Paper arxiv.org/pdf/2303.15904.pdf
😎Project www.vis.xyz/pub/maskfreevis/
😎Code github.com/SysCV/maskfreevis
👉ETH Z unveils MaskFreeVIS: novel high-performing VIS without any mask annotations.
😎Review https://bit.ly/3Wg7CQB
😎Paper arxiv.org/pdf/2303.15904.pdf
😎Project www.vis.xyz/pub/maskfreevis/
😎Code github.com/SysCV/maskfreevis
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🀄 Drag-GAN: user-friendly image-manipulation 🀄
👉 Manual deforming of (real and generated) images over pose, shape, expression and layout.
😎Review https://bit.ly/3BFyXlR
😎Paper arxiv.org/pdf/2305.10973.pdf
😎Project vcai.mpi-inf.mpg.de/projects/DragGAN
😎Code github.com/XingangPan/DragGAN
👉 Manual deforming of (real and generated) images over pose, shape, expression and layout.
😎Review https://bit.ly/3BFyXlR
😎Paper arxiv.org/pdf/2305.10973.pdf
😎Project vcai.mpi-inf.mpg.de/projects/DragGAN
😎Code github.com/XingangPan/DragGAN
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🗺️ AI-generated stereotypical men 🗺️
👉A thread about generating stereotypical person from 15 countries all around the world. And yes, Italian love Pizza.
😎 More https://bit.ly/3oo0t4c
👉A thread about generating stereotypical person from 15 countries all around the world. And yes, Italian love Pizza.
😎 More https://bit.ly/3oo0t4c
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🍶 AVOS Multiscale Encoder-Decoder ViT 🍶
👉 MED-VT, world's first Multiscale Encoder Decoder Video Transformer for AVOS
😎Review https://bit.ly/3MohFi1
😎Paper arxiv.org/pdf/2304.05930.pdf
😎Project rkyuca.github.io/medvt
😎Code github.com/rkyuca/medvt
👉 MED-VT, world's first Multiscale Encoder Decoder Video Transformer for AVOS
😎Review https://bit.ly/3MohFi1
😎Paper arxiv.org/pdf/2304.05930.pdf
😎Project rkyuca.github.io/medvt
😎Code github.com/rkyuca/medvt
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🌊 Neural Dynamic Image-Based Rendering 🌊
👉 DynIBaR: synthesizing novel views from monocular video depicting a complex dynamic scene.
😎Review https://t.ly/90Kw
😎Paper arxiv.org/pdf/2211.11082.pdf
😎Project https://dynibar.github.io/
😎Code github.com/google/dynibar
👉 DynIBaR: synthesizing novel views from monocular video depicting a complex dynamic scene.
😎Review https://t.ly/90Kw
😎Paper arxiv.org/pdf/2211.11082.pdf
😎Project https://dynibar.github.io/
😎Code github.com/google/dynibar
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🦁 Open Semantic Segmentation 🦁
👉SSSegmentation: open source supervised semantic segmentation toolbox based on #PyTorch
😎Review https://t.ly/ZE9q
😎Paper arxiv.org/pdf/2305.17091.pdf
😎Code github.com/SegmentationBLWX/sssegmentation
👉SSSegmentation: open source supervised semantic segmentation toolbox based on #PyTorch
😎Review https://t.ly/ZE9q
😎Paper arxiv.org/pdf/2305.17091.pdf
😎Code github.com/SegmentationBLWX/sssegmentation
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🎗️ 4D Humans with Transformers 🎗️
👉Novel approach to reconstruct and track humans (even in unusual poses)
😎Review https://t.ly/XGv_
😎Paper arxiv.org/pdf/2305.20091.pdf
😎Project shubham-goel.github.io/4dhumans/#
😎Code github.com/shubham-goel/4D-Humans
👉Novel approach to reconstruct and track humans (even in unusual poses)
😎Review https://t.ly/XGv_
😎Paper arxiv.org/pdf/2305.20091.pdf
😎Project shubham-goel.github.io/4dhumans/#
😎Code github.com/shubham-goel/4D-Humans
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🗽 Neuralangelo Digital Twins. INSANE🗽
👉 A novel framework from #Nvidia for Hi-Fi 3D Digital twins.
😎Review https://t.ly/rxoF4
😎Project research.nvidia.com/labs/dir/neuralangelo
😎Paper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
👉 A novel framework from #Nvidia for Hi-Fi 3D Digital twins.
😎Review https://t.ly/rxoF4
😎Project research.nvidia.com/labs/dir/neuralangelo
😎Paper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
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🦜 ColorDiffuser: Text-to-Video Colorization 🦜
👉HK University unveils ColorDiffuser: adapting pre-trained text-to-image latent diffusion model for video colorization
😎Review https://t.ly/XGv_
😎Paper arxiv.org/pdf/2306.01732.pdf
😎Project colordiffuser.github.io/
😎Code github.com/ColorDiffuser/ColorDiffuser
👉HK University unveils ColorDiffuser: adapting pre-trained text-to-image latent diffusion model for video colorization
😎Review https://t.ly/XGv_
😎Paper arxiv.org/pdf/2306.01732.pdf
😎Project colordiffuser.github.io/
😎Code github.com/ColorDiffuser/ColorDiffuser
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🌻 Extending Mona Lisa with AI 🌻
👉 A guy on Reddit extends Mona Lisa Painting with #Photoshop AI. The result is surprising.
😎More https://t.ly/j_2r
👉 A guy on Reddit extends Mona Lisa Painting with #Photoshop AI. The result is surprising.
😎More https://t.ly/j_2r
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🏸 Segment Anything in HQ 🏸
👉HQ-SAM: SAM with the ability to accurately segment objects, maintaining promptable design, efficiency, zero-shot generalizability
😎Review https://t.ly/GxX5B
😎Paper arxiv.org/pdf/2306.01567.pdf
😎Models github.com/SysCV/SAM-HQ
👉HQ-SAM: SAM with the ability to accurately segment objects, maintaining promptable design, efficiency, zero-shot generalizability
😎Review https://t.ly/GxX5B
😎Paper arxiv.org/pdf/2306.01567.pdf
😎Models github.com/SysCV/SAM-HQ
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🌈 Track Everything Everywhere 🌈
👉#Google unveils OmniMotion: full-length motion tracking for every pixel in every frame of video.
😎Review https://t.ly/Krvw
😎Paper arxiv.org/pdf/2306.05422.pdf
😎Project omnimotion.github.io/
😎Demo omnimotion.github.io/#interactive_demo
😎Code github.com/qianqianwang68/omnimotion
👉#Google unveils OmniMotion: full-length motion tracking for every pixel in every frame of video.
😎Review https://t.ly/Krvw
😎Paper arxiv.org/pdf/2306.05422.pdf
😎Project omnimotion.github.io/
😎Demo omnimotion.github.io/#interactive_demo
😎Code github.com/qianqianwang68/omnimotion
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👁️ Scene Five: Through Her Eyes 👁️
👉 #3D scene reconstruction of what a person is observing using only the reflections of their eyes
😎Review https://t.ly/uBO6
😎Paper arxiv.org/pdf/2306.09348.pdf
😎Project https://world-from-eyes.github.io/
👉 #3D scene reconstruction of what a person is observing using only the reflections of their eyes
😎Review https://t.ly/uBO6
😎Paper arxiv.org/pdf/2306.09348.pdf
😎Project https://world-from-eyes.github.io/
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🧿 NeRF-Supervised Deep Stereo 🧿
👉A novel pioneering pipeline for training deep stereo networks WITH NO ground-truth
😎Review https://t.ly/c7j-
😎Project nerfstereo.github.io/
😎Dataset https://amsacta.unibo.it/id/eprint/7218/
😎Code github.com/fabiotosi92/NeRF-Supervised-Deep-Stereo
😎Paper https://openaccess.thecvf.com/content/CVPR2023/papers/Tosi_NeRF-Supervised_Deep_Stereo_CVPR_2023_paper.pdf
👉A novel pioneering pipeline for training deep stereo networks WITH NO ground-truth
😎Review https://t.ly/c7j-
😎Project nerfstereo.github.io/
😎Dataset https://amsacta.unibo.it/id/eprint/7218/
😎Code github.com/fabiotosi92/NeRF-Supervised-Deep-Stereo
😎Paper https://openaccess.thecvf.com/content/CVPR2023/papers/Tosi_NeRF-Supervised_Deep_Stereo_CVPR_2023_paper.pdf
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🫣 Text-Guided Adversarial Makeup 🫣
👉Novel facial privacy protection via adversarial latent codes. Makeup vs Face Recognition.
😎Review https://t.ly/pBCP
😎Paper arxiv.org/pdf/2306.10008.pdf
😎Code github.com/fahadshamshad/Clip2Protect
👉Novel facial privacy protection via adversarial latent codes. Makeup vs Face Recognition.
😎Review https://t.ly/pBCP
😎Paper arxiv.org/pdf/2306.10008.pdf
😎Code github.com/fahadshamshad/Clip2Protect
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🦷 Few-Shot Geometry-Aware Keypoints 🦷
👉UBC (+Flawless AI) unveils the new SOTA in semantic keypoints localization. Suitable for faces, animals, cars, mouth, teeth & more
😎Review https://t.ly/-0qN
😎Paper arxiv.org/pdf/2303.17216.pdf
😎Project xingzhehe.github.io/FewShot3DKP/
👉UBC (+Flawless AI) unveils the new SOTA in semantic keypoints localization. Suitable for faces, animals, cars, mouth, teeth & more
😎Review https://t.ly/-0qN
😎Paper arxiv.org/pdf/2303.17216.pdf
😎Project xingzhehe.github.io/FewShot3DKP/
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