# LongShortNet: Exploring Temporal and Semantic Features Fusion in Streaming Perception

arXiv: https://arxiv.org/abs/2210.15518 · HTML: https://mlsanity.com/paper/2210.15518/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 40 references that are in the map.
- First posted on arXiv 27 Oct 2022.

## Builds on (most cited first, 24 of 24)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [YOLOX: Exceeding YOLO Series in 2021](https://mlsanity.com/paper/2107.08430/) (2021)
- [Path Aggregation Network for Instance Segmentation](https://mlsanity.com/paper/1803.01534/) (2018)
- [Deep Feature Flow for Video Recognition](https://mlsanity.com/paper/1611.07715/) (2016)
- [Flow-Guided Feature Aggregation for Video Object Detection](https://mlsanity.com/paper/1703.10025/) (2017)
- [Memory Enhanced Global-Local Aggregation for Video Object Detection](https://mlsanity.com/paper/2003.12063/) (2020)
- [Sequence Level Semantics Aggregation for Video Object Detection](https://mlsanity.com/paper/1907.06390/) (2019)
- [Relation Distillation Networks for Video Object Detection](https://mlsanity.com/paper/1908.09511/) (2019)
- [Seq-NMS for Video Object Detection](https://mlsanity.com/paper/1602.08465/) (2016)
- [Towards High Performance Video Object Detection](https://mlsanity.com/paper/1711.11577/) (2017)
- [Object Detection in Video with Spatiotemporal Sampling Networks](https://mlsanity.com/paper/1803.05549/) (2018)
- [Rethinking Spatial Invariance of Convolutional Networks for Object Counting](https://mlsanity.com/paper/2206.05253/) (2022)
- [Video Object Detection with an Aligned Spatial-Temporal Memory](https://mlsanity.com/paper/1712.06317/) (2017)
- [End-to-End Video Object Detection with Spatial-Temporal Transformers](https://mlsanity.com/paper/2105.10920/) (2021)
- [TF-Blender: Temporal Feature Blender for Video Object Detection](https://mlsanity.com/paper/2108.05821/) (2021)
- [Learning Spatial Awareness to Improve Crowd Counting](https://mlsanity.com/paper/1909.07057/) (2019)
- [Real-time Object Detection for Streaming Perception](https://mlsanity.com/paper/2203.12338/) (2022)
- [AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling](https://mlsanity.com/paper/1902.02910/) (2019)
- [GSRFormer: Grounded Situation Recognition Transformer with Alternate Semantic Attention Refinement](https://mlsanity.com/paper/2208.08965/) (2022)
- [PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection](https://mlsanity.com/paper/2209.02242/) (2022)
- [QueryProp: Object Query Propagation for High-Performance Video Object Detection](https://mlsanity.com/paper/2207.10959/) (2022)
- [Object Detection in Videos by High Quality Object Linking](https://mlsanity.com/paper/1801.09823/) (2018)
- [Decoupling Localization and Classification in Single Shot Temporal Action Detection](https://mlsanity.com/paper/1904.07442/) (2019)

## Built on by (most cited first, 12 of 12)

- [DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving](https://mlsanity.com/paper/2303.17144/) (2023)
- [PoSynDA: Multi-Hypothesis Pose Synthesis Domain Adaptation for Robust 3D Human Pose Estimation](https://mlsanity.com/paper/2308.09678/) (2023)
- [Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment](https://mlsanity.com/paper/2308.08696/) (2023)
- [KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration](https://mlsanity.com/paper/2305.16437/) (2023)
- [Towards Latency-Aware 3D Streaming Perception for Autonomous Driving](https://mlsanity.com/paper/2504.19115/) (2025)
- [OoDDINO:A Multi-level Framework for Anomaly Segmentation on Complex Road Scenes](https://mlsanity.com/paper/2507.01455/) (2025)
- [Fast Fourier Inception Networks for Occluded Video Prediction](https://mlsanity.com/paper/2306.10346/) (2023)
- [DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception](https://mlsanity.com/paper/2403.05050/) (2024)
- [Real-time Stereo-based 3D Object Detection for Streaming Perception](https://mlsanity.com/paper/2410.12394/) (2024)
- [4DSegStreamer: Streaming 4D Panoptic Segmentation via Dual Threads](https://mlsanity.com/paper/2510.17664/) (2025)
- [Bend the Clock: Predicting Ahead to Beat Latency in Event-Based Object Detection](https://mlsanity.com/paper/2609.26919/) (2026)
- [Rethinking Streaming-Perception Evaluation on Heterogeneous Edge Platforms](https://mlsanity.com/paper/2610.05578/) (2026)

## Abstract (arXiv)

Streaming perception is a critical task in autonomous driving that requires balancing the latency and accuracy of the autopilot system. However, current methods for streaming perception are limited as they only rely on the current and adjacent two frames to learn movement patterns. This restricts their ability to model complex scenes, often resulting in poor detection results. To address this limitation, we propose LongShortNet, a novel dual-path network that captures long-term temporal motion and integrates it with short-term spatial semantics for real-time perception. LongShortNet is notable as it is the first work to extend long-term temporal modeling to streaming perception, enabling spatiotemporal feature fusion. We evaluate LongShortNet on the challenging Argoverse-HD dataset and demonstrate that it outperforms existing state-of-the-art methods with almost no additional computational cost.