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Found 4 papers, 4 papers with code
DINO in the Room: Leveraging 2D Foundation Models for 3D Segmentation
Vision foundation models (VFMs) trained on large-scale image datasets provide high-quality features that have significantly advanced 2D visual recognition.
Ranked #1 on
3D Semantic Segmentation
on ScanNet++
Fine-Tuning Image-Conditional Diffusion Models is Easier than You Think
Recent work showed that large diffusion models can be reused as highly precise monocular depth estimators by casting depth estimation as an image-conditional image generation task.
Ranked #1 on
Surface Normals Estimation
on IBims-1
Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
A holistic 3Dunderstanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation.
Point2Vec for Self-Supervised Representation Learning on Point Clouds
Recently, the self-supervised learning framework data2vec has shown inspiring performance for various modalities using a masked student-teacher approach.
Ranked #5 on
3D Point Cloud Classification
on ModelNet40
(using extra training data)
3D Part Segmentation
Few-Shot 3D Point Cloud Classification
+3
