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StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 137 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 53 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 19 -
Priority Sampling of Large Language Models for Compilers
Paper • 2402.18734 • Published • 17
Collections
Discover the best community collections!
Collections including paper arxiv:2402.17427
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VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction
Paper • 2402.17427 • Published • 10 -
Disentangled 3D Scene Generation with Layout Learning
Paper • 2402.16936 • Published • 11 -
RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPS
Paper • 2403.13806 • Published • 18 -
DreamCar: Leveraging Car-specific Prior for in-the-wild 3D Car Reconstruction
Paper • 2407.16988 • Published • 8
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SHINOBI: Shape and Illumination using Neural Object Decomposition via BRDF Optimization In-the-wild
Paper • 2401.10171 • Published • 14 -
Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
Paper • 2401.14257 • Published • 11 -
pix2gestalt: Amodal Segmentation by Synthesizing Wholes
Paper • 2401.14398 • Published • 10 -
AGG: Amortized Generative 3D Gaussians for Single Image to 3D
Paper • 2401.04099 • Published • 9
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541
DreamGaussian
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VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction
Paper • 2402.17427 • Published • 10 -
BirdNeRF: Fast Neural Reconstruction of Large-Scale Scenes From Aerial Imagery
Paper • 2402.04554 • Published -
GaussianPro: 3D Gaussian Splatting with Progressive Propagation
Paper • 2402.14650 • Published • 7
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MVDream: Multi-view Diffusion for 3D Generation
Paper • 2308.16512 • Published • 102 -
Learning Disentangled Avatars with Hybrid 3D Representations
Paper • 2309.06441 • Published • 4 -
Dynamic Mesh-Aware Radiance Fields
Paper • 2309.04581 • Published • 6 -
Towards Practical Capture of High-Fidelity Relightable Avatars
Paper • 2309.04247 • Published • 9