wuke

[wuke @wuke20010216]

Welcome to check out our latest work on 6D pose estimation—DynOPETs! 📣
Our dataset features both the camera and objects in motion, with assets and scenarios that are more extensive and diverse than previous datasets.💕

🤖Project page: https://t.co/pPYa4A16J2

[AI Bites | YouTube Channel @ai_bites]

Given arbitrary scene and open-domain rigged objects, A3Syn synthesizes articulation that respects the affordance and context.
The task is incredibly challenging due to the lack of training data, and we do not make any topological assumptions about the open-domain rigs. The work proposes using 2D inpainting diffusion model and several control techniques to synthesize in-context affordance information.

Paper: Towards Affordance-Aware Articulation
Synthesis for Rigged Objects
Link: https://t.co/ZZnOFOzIC7
Project: https://t.co/kQghiYaKyo

#AI #AI美女 #LLMs #deeplearning #machinelearning #3D #generativeAI

[wuke @wuke20010216]

@ArnoMeng Thanks for sharing VINGs-Mono~

[Xiangting (Martin) Meng @ArnoMeng]

Wu et al. VINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes
https://t.co/jbCgK53q1g
Shared by: https://t.co/UKAeo3E282

[Angela Dai @angelaqdai]

Excited to announce ScanNet++ v2!🎉

@chandan__yes and @liuyuehcheng have been working tirelessly to bring:
🔹1006 high-fidelity 3D scans
🔹+ DSLR & iPhone captures
🔹+ rich semantics
Elevating 3D scene understanding to the next level!🚀

w/ @MattNiessner
https://t.co/QayR1S8KZZ