activity
20232025
most citedOpenStereo: A Comprehensive Benchmark for Stereo Matching and Strong Baseline

6 citations · 7 across the 10 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

SURDS: Benchmarking Spatial Understanding and Reasoning in Driving Scenarios with Vision Language Models

Xianda Guo, Ruijun Zhang, Yiqun Duan +7

Accurate spatial reasoning in outdoor environments - covering geometry, object pose, and inter-object relationships - is fundamental to downstream tasks such as mapping, motion for…

eess.SP2024

BELT-2: Bootstrapping EEG-to-Language representation alignment for multi-task brain decoding

Jinzhao Zhou, Yiqun Duan, Fred Chang +3

The remarkable success of large language models (LLMs) across various multi-modality applications is well established. However, integrating large language models with humans, or br…

cs.RO2024

Enhancing End-to-End Autonomous Driving Systems Through Synchronized Human Behavior Data

Yiqun Duan, Zhuoli Zhuang, Jinzhao Zhou +3

This paper presents a pioneering exploration into the integration of fine-grained human supervision within the autonomous driving domain to enhance system performance. The current…

cs.LG2024

Masked EEG Modeling for Driving Intention Prediction

Jinzhao Zhou, Justin Sia, Yiqun Duan +3

Driving under drowsy conditions significantly escalates the risk of vehicular accidents. Although recent efforts have focused on using electroencephalography to detect drowsiness,…

cs.CL2024

Towards Linguistic Neural Representation Learning and Sentence Retrieval from Electroencephalogram Recordings

Jinzhao Zhou, Yiqun Duan, Ziyi Zhao +4

Decoding linguistic information from non-invasive brain signals using EEG has gained increasing research attention due to its vast applicational potential. Recently, a number of wo…

cs.CV2024★ 1 cited

MaskFuser: Masked Fusion of Joint Multi-Modal Tokenization for End-to-End Autonomous Driving

Yiqun Duan, Xianda Guo, Zheng Zhu +3

Current multi-modality driving frameworks normally fuse representation by utilizing attention between single-modality branches. However, the existing networks still suppress the dr…