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20182026
most citedEvent-Based Fusion for Motion Deblurring with Cross-modal Attention

178 citations · 569 across the 193 of their papers we have counts for

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Showing 2024Show all

30 papers · 1 filter

cs.CV2024

Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization

Kunyu Peng, Di Wen, M. Saquib Sarfraz +7

Open-Set Domain Generalization (OSDG) is a challenging task requiring models to accurately predict familiar categories while minimizing confidence for unknown categories to effecti…

cs.HC2024★ 2 cited

ObjectFinder: An Open-Vocabulary Assistive System for Interactive Object Search by Blind People

Ruiping Liu, Jiaming Zhang, Angela Schön +6

Searching for objects in unfamiliar scenarios is a challenging task for blind people. It involves specifying the target object, detecting it, and then gathering detailed informatio…

eess.IV2024

Towards Dependable Optical Flow: Benchmarks for Real-World Spatiotemporal Corruptions

Zhonghua Yi, Hao Shi, Qi Jiang +5

Optical flow estimation is a fundamental task in dynamic scene understanding and computer vision. While recent deep models achieve impressive accuracy on clean benchmarks, their ro…

cs.CV2024

Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation

Xu Zheng, Haiwei Xue, Jialei Chen +6

Simultaneously using multimodal inputs from multiple sensors to train segmentors is intuitively advantageous but practically challenging. A key challenge is unimodal bias, where mu…

cs.CV2024

EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local Feature Extraction and Matching for Event-Image Data

Zhonghua Yi, Hao Shi, Qi Jiang +5

Event cameras, with high temporal resolution and high dynamic range, have limited research on the inter-modality local feature extraction and matching of event-image data. We propo…

cs.LG2024★ 1 cited

Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler

Kunyu Peng, Di Wen, Kailun Yang +6

In Open-Set Domain Generalization (OSDG), the model is exposed to both new variations of data appearance (domains) and open-set conditions, where both known and novel categories ar…