Trending Research
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
HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D Reconstruction
Reconstructing 3D objects is an important computer vision task that has wide application in AR/VR.
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
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
Vegetebird/StridedTransformer-Pose3D
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The modified VTE is termed as Strided Transformer Encoder (STE), which is built upon the outputs of VTE.
Ranked #1 on
3D Human Pose Estimation
on HumanEva-I
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case
clementchadebec/benchmark_VAE
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In recent years, deep generative models have attracted increasing interest due to their capacity to model complex distributions.
Evaluating Large Language Models Trained on Code
We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities.
Ranked #1 on
Code Generation
on APPS
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
We introduce \textit{Nocturne}, a new 2D driving simulator for investigating multi-agent coordination under partial observability.
The ArtBench Dataset: Benchmarking Generative Models with Artworks
We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation.
OmniXAI: A Library for Explainable AI
We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to address the pain points of understanding and interpreting the decisions made by machine learning (ML) in practice.
I M Avatar: Implicit Morphable Head Avatars from Videos
zhengyuf/imavatar
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CVPR 2022
Traditional 3D morphable face models (3DMMs) provide fine-grained control over expression but cannot easily capture geometric and appearance details.
