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Found 5 papers, 2 papers with code
MLLMs are Deeply Affected by Modality Bias
These findings highlight the need for balanced training strategies and model architectures to better integrate multiple modalities in MLLMs.
Seamless Detection: Unifying Salient Object Detection and Camouflaged Object Detection
To this end, inspired by the agreeable nature of binary segmentation for SOD and COD, we propose a Contrastive Distillation Paradigm (CDP) to distil the foreground from the background, facilitating the identification of salient and camouflaged objects amidst their surroundings.
A Fuzzy Reinforcement LSTM-based Long-term Prediction Model for Fault Conditions in Nuclear Power Plants
Early fault detection and timely maintenance scheduling can significantly mitigate operational risks in NPPs and enhance the reliability of operator decision-making.
Part-Whole Relational Fusion Towards Multi-Modal Scene Understanding
To tackle the challenge, in this paper, we propose a Part-Whole Relational Fusion (PWRF) framework.
PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment
Monocular 3D lane detection is essential for a reliable autonomous driving system and has recently been rapidly developing.
Ranked #3 on
3D Lane Detection
on OpenLane
