Trending Research
Pen and Paper Exercises in Machine Learning
This is a collection of (mostly) pen-and-paper exercises in machine learning.
Multi-Graph Fusion Networks for Urban Region Embedding
wushangbin/mgfn
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Human mobility data contains rich but abundant information, which yields to the comprehensive region embeddings for cross domain tasks.
ProGen2: Exploring the Boundaries of Protein Language Models
Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial intelligence-driven protein design.
Denoised MDPs: Learning World Models Better Than the World Itself
The ability to separate signal from noise, and reason with clean abstractions, is critical to intelligence.
Ivy: Templated Deep Learning for Inter-Framework Portability
ivy-dl/ivy
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We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks.
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
We present the Pathways Autoregressive Text-to-Image (Parti) model, which generates high-fidelity photorealistic images and supports content-rich synthesis involving complex compositions and world knowledge.
Ranked #1 on
Text-to-Image Generation
on COCO
EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
tjiiv-cprg/epro-pnp
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CVPR 2022
The 2D-3D coordinates and corresponding weights are treated as intermediate variables learned by minimizing the KL divergence between the predicted and target pose distribution.
Ranked #4 on
6D Pose Estimation using RGB
on LineMOD
BokehMe: When Neural Rendering Meets Classical Rendering
juewenpeng/bokehme
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CVPR 2022
Based on this formulation, we implement the classical renderer by a scattering-based method and propose a two-stage neural renderer to fix the erroneous areas from the classical renderer.
Zero-Shot Text-to-Image Generation
Text-to-image generation has traditionally focused on finding better modeling assumptions for training on a fixed dataset.
Ranked #12 on
Text-to-Image Generation
on COCO
(using extra training data)
LViT: Language meets Vision Transformer in Medical Image Segmentation
huanglizi/lvit
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In our model, medical text annotation is introduced to compensate for the quality deficiency in image data.
