👹AI and the Everything in the Whole Wide World Benchmark👹

👉Last week Yann LeCun said something like "LLMs will not reach human intelligence". It's clear the on-going #deeplearning is not ready for "general AI", a "radical alternative" is necessary to create a “superintelligence”.

👉Review https://t.ly/isdxM
👉News https://lnkd.in/dFraieZS
👉Paper https://lnkd.in/da-7PnVT

📞FacET: VideoCall Change Your Expression📞

👉Columbia University unveils FacET: discovering behavioral differences between conversing face-to-face (F2F) and on video-calls (VCs).

👉Review https://t.ly/qsQmt
👉Paper arxiv.org/pdf/2406.00955
👉Project facet.cs.columbia.edu/
👉Repo (empty) github.com/stellargo/facet

🚙 UA-Track: Uncertainty-Aware MOT🚙

👉UA-Track: novel Uncertainty-Aware 3D MOT framework which tackles the uncertainty problem from multiple aspects. Code announced, not released yet.

👉Review https://t.ly/RmVSV
👉Paper https://arxiv.org/pdf/2406.02147
👉Project https://liautoad.github.io/ua-track-website

🧊 Universal 6D Pose/Tracking 🧊

👉Omni6DPose is a novel dataset for 6D Object Pose with 1.5M+ annotations. Extra: GenPose++, the novel SOTA in category-level 6D estimation/tracking thanks to two pivotal improvements.

👉Review https://t.ly/Ywgl1
👉Paper arxiv.org/pdf/2406.04316
👉Project https://lnkd.in/dHBvenhX
👉Lib https://lnkd.in/d8Yc-KFh

👗 SOTA Multi-Garment VTOn Editing 👗

👉#Google (+UWA) unveils M&M VTO, novel mix 'n' match virtual try-on that takes as input multiple garment images, text description for garment layout and an image of a person. It's the new SOTA both qualitatively and quantitatively. Impressive results!

👉Review https://t.ly/66mLN
👉Paper arxiv.org/pdf/2406.04542
👉Project https://mmvto.github.io

👑 Kling AI vs. OpenAI Sora 👑

👉Kling: the ultimate Chinese text-to-video model - rival to #OpenAI’s Sora. No papers or tech info to check, but stunning results from the official site.

👉Review https://t.ly/870DQ
👉Paper ???
👉Project https://kling.kuaishou.com/

🍉 MASA: MOT Anything By SAM 🍉

👉MASA: Matching Anything by Segmenting Anything pipeline to learn object-level associations from unlabeled images of any domain. An universal instance appearance model for matching any objects in any domain. Source code in June 💙

👉Review https://t.ly/pKdEV
👉Paper https://lnkd.in/dnjuT7xm
👉Project https://lnkd.in/dYbWzG4E
👉Code https://lnkd.in/dr5BJCXm

🎹 PianoMotion10M for gen-hands 🎹

👉PianoMotion10M: 116 hours of piano playing videos from a bird’s-eye view with 10M+ annotated hand poses. A big contribution in hand motion generation. Code & Dataset released💙

👉Review https://t.ly/_pKKz
👉Paper arxiv.org/pdf/2406.09326
👉Code https://lnkd.in/dcBP6nvm
👉Project https://lnkd.in/d_YqZk8x
👉Dataset https://lnkd.in/dUPyfNDA

📫MeshPose: DensePose+HMR📫

👉MeshPose: novel approach to jointly tackle DensePose and Human Mesh Reconstruction in a while. A natural fit for #AR applications requiring real-time mobile inference.

👉Review https://t.ly/a-5uN
👉Paper arxiv.org/pdf/2406.10180
👉Project https://meshpose.github.io/

🌵 RobustSAM for Degraded Images 🌵

👉RobustSAM, the evolution of SAM for degraded images; enhancing the SAM’s performance on low-quality pics while preserving prompt-ability & zeroshot generalization. Dataset & Code released💙

👉Review https://t.ly/mnyyG
👉Paper arxiv.org/pdf/2406.09627
👉Project robustsam.github.io
👉Code github.com/robustsam/RobustSAM

🧤HOT3D Hand/Object Tracking🧤

👉#Meta opens a novel egocentric dataset for 3D hand & object tracking. A new benchmark for vision-based understanding of 3D hand-object interactions. Dataset available 💙

👉Review https://t.ly/cD76F
👉Paper https://lnkd.in/e6_7UNny
👉Data https://lnkd.in/e6P-sQFK

💦 Self-driving in wet conditions 💦

👉BMW SemanticSpray: novel dataset contains scenes in wet surface conditions captured by camera, LiDAR and radar. Camera: 2D Boxes | LiDAR: 3D Boxes, Semantic Labels | Radar: Semantic Labels.

👉Review https://t.ly/8S93j
👉Paper https://lnkd.in/dnN5MCZC
👉Project https://lnkd.in/dkUaxyEF
👉Data https://lnkd.in/ddhkyXv8

🌱 TokenHMR : new 3D human pose SOTA 🌱

👉TokenHMR is the new SOTA HPS method mixing 2D keypoints and 3D pose accuracy, thus leveraging Internet data without known camera parameters. It's the new SOTA by a large margin.

👉Review https://t.ly/K9_8n
👉Paper arxiv.org/pdf/2404.16752
👉Project tokenhmr.is.tue.mpg.de/
👉Code github.com/saidwivedi/TokenHMR

🤓Glasses-Removal in Videos🤓

👉Lightricks unveils a novel method able to receive an input video of a person wearing glasses, and removes the glasses preserving the ID. It works even with reflections, heavy makeup, and blinks. Code announced, not yet released.

👉Review https://t.ly/Hgs2d
👉Paper arxiv.org/pdf/2406.14510
👉Project https://v-lasik.github.io/
👉Code github.com/v-lasik/v-lasik-code

🧬Event-driven SuperResolution🧬

👉USTC unveils EvTexture, the first VSR method that utilizes event signals for texture enhancement. It leverages high-freq details of events to better recover texture in VSR. Code available💙

👉Review https://t.ly/zlb4c
👉Paper arxiv.org/pdf/2406.13457
👉Code github.com/DachunKai/EvTexture

🐻StableNormal: Stable/Sharp Normal🐻

👉Alibaba unveils StableNormal, a novel method which tailors the diffusion priors for monocular normal estimation. Hugging Face demo is available💙

👉Review https://t.ly/FPJlG
👉Paper https://arxiv.org/pdf/2406.16864
👉Demo https://huggingface.co/Stable-X

🍦Geometry Guided Depth🍦

👉Depth and #3D reconstruction which can take as input, where available, previously-made estimates of the scene’s geometry

👉Review https://lnkd.in/dMgakzWm
👉Paper https://arxiv.org/pdf/2406.18387
👉Repo (empty) https://github.com/nianticlabs/DoubleTake

🌮MeshAnything with Transformers🌮

👉MeshAnything converts any 3D representation into Artist-Created Meshes (AMs), i.e., meshes created by human artists. It can be combined with various 3D asset production pipelines, such as 3D reconstruction and generation, to transform their results into AMs that can be seamlessly applied in the 3D industry. Source Code available💙

👉Review https://t.ly/HvkD4
👉Paper arxiv.org/pdf/2406.10163
👉Code github.com/buaacyw/MeshAnything

🌾LLaNA: NeRF-LLM assistant🌾

👉UniBO unveils LLaNA; novel Multimodal-LLM that understands and reasons on an input NeRF. It processes directly the NeRF weights and performs tasks such as captioning, Q&A, & zero-shot classification of NeRFs.

👉Review https://t.ly/JAfhV
👉Paper arxiv.org/pdf/2406.11840
👉Project andreamaduzzi.github.io/llana/
👉Code & Data coming

🔥 Depth Anything v2 is out! 🔥

👉 Depth Anything V2: outperforming V1 in robustness and fine-grained details. Trained w/ 595K synthetic labels and 62M+ real unlabeled images, the new SOTA in MDE. Code & Models available💙

👉Review https://t.ly/QX9Nu
👉Paper arxiv.org/pdf/2406.09414
👉Project depth-anything-v2.github.io/
👉Repo github.com/DepthAnything/Depth-Anything-V2
👉Data huggingface.co/datasets/depth-anything/DA-2K