Trending Research
OnePose: One-Shot Object Pose Estimation without CAD Models
We propose a new method named OnePose for object pose estimation.
SymForce: Symbolic Computation and Code Generation for Robotics
We present SymForce, a library for fast symbolic computation, code generation, and nonlinear optimization for robotics applications like computer vision, motion planning, and controls.
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding.
Ranked #1 on
Text-to-Image Generation
on COCO
(using extra training data)
PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit
PaddleSpeech is an open-source all-in-one speech toolkit.
Automatic Speech Recognition
Environmental Sound Classification
+8
MuJoCo: A physics engine for model-based control
To facilitate optimal control applications and in particular sampling and finite differencing, the dynamics can be evaluated for different states and controls in parallel.
Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality
implus/um-mae
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Masked AutoEncoder (MAE) has recently led the trends of visual self-supervision area by an elegant asymmetric encoder-decoder design, which significantly optimizes both the pre-training efficiency and fine-tuning accuracy.
Ranked #16 on
Object Detection
on COCO minival
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.
Planning with Diffusion for Flexible Behavior Synthesis
jannerm/diffuser
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Model-based reinforcement learning methods often use learning only for the purpose of estimating an approximate dynamics model, offloading the rest of the decision-making work to classical trajectory optimizers.
BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
Specifically, BEVerse first performs shared feature extraction and lifting to generate 4D BEV representations from multi-timestamp and multi-view images.
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
hsouri/bayesiantransferlearning
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Deep learning is increasingly moving towards a transfer learning paradigm whereby large foundation models are fine-tuned on downstream tasks, starting from an initialization learned on the source task.
