most citedRethinking Population-assisted Off-policy Reinforcement Learning

10 citations · 21 across the 9 of their papers we have counts for

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cs.CV20243 cited

A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic Segmentation

Yifan Zhao, Zhenyu Liang, Zhichao Lu +1

As one of the emerging challenges in Automated Machine Learning, the Hardware-aware Neural Architecture Search (HW-NAS) tasks can be treated as black-box multi-objective optimizati…

cs.CV2023

Seed Feature Maps-based CNN Models for LEO Satellite Remote Sensing Services

Zhichao Lu, Chuntao Ding, Shangguang Wang +3

Deploying high-performance convolutional neural network (CNN) models on low-earth orbit (LEO) satellites for rapid remote sensing image processing has attracted significant interes…

cs.CV2023

Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives

Chuntao Ding, Zhichao Lu, Shangguang Wang +2

Multi-task learning (MTL) seeks to learn a single model to accomplish multiple tasks by leveraging shared information among the tasks. Existing MTL models, however, have been known…

cs.CV2023

Accelerating Vision-Language Pretraining with Free Language Modeling

Teng Wang, Yixiao Ge, Feng Zheng +4

The state of the arts in vision-language pretraining (VLP) achieves exemplary performance but suffers from high training costs resulting from slow convergence and long training tim…

cs.CV20237 cited

Learning Grounded Vision-Language Representation for Versatile Understanding in Untrimmed Videos

Teng Wang, Jinrui Zhang, Feng Zheng +3

Joint video-language learning has received increasing attention in recent years. However, existing works mainly focus on single or multiple trimmed video clips (events), which make…

cs.CV20222 cited

Surrogate-assisted Multi-objective Neural Architecture Search for Real-time Semantic Segmentation

Zhichao Lu, Ran Cheng, Shihua Huang +3

The architectural advancements in deep neural networks have led to remarkable leap-forwards across a broad array of computer vision tasks. Instead of relying on human expertise, ne…