Omkar2118/datasets huggingface dataset:
lilGym

**lilGym** is a benchmark for language-conditioned reinforcement learning in visual environment based on 2,661 highly-compositional human-written natural language statements grounded in an interactive visual environment. Each statement is paired with multiple start states and reward functions to form thousands of distinct Markov Decision Processes of varying difficulty.

Source: [lilGym: Natural Language Visual Reasoning with Reinforcement Learning](https://arxiv.org/pdf/2211.01994v2.pdf)

Image Source: [https://github.com/lil-lab/lilgym](https://github.com/lil-lab/lilgym)

Introducing paper: lilGym: Natural Language Visual Reasoning with Reinforcement Learning
Autonomous-driving Streaming Perception Benchmarrk

The **Autonomous-driving StreAming Perception** (ASAP) benchmark is a benchmark to evaluate the online performance of vision-centric perception in autonomous driving. It extends the 2Hz annotated nuScenes dataset by generating high-frame-rate labels for the 12Hz raw images.

Source: [Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark](https://arxiv.org/pdf/2212.08914v1.pdf)

Image Source: [https://github.com/jeffwang987/asap](https://github.com/jeffwang987/asap)

Introducing paper: Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark