Introduces P-RWKV block and PointER self-supervised framework to adapt RWKV for efficient 3D point cloud representation learning.
arXiv preprint arXiv:2406.19369 (2024)
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PestVL-Net combines an RWKV visual backbone with saliency-guided window partitioning and MLLM-derived linguistic priors via multimodal chain-of-thought to enable fine-grained multimodal pest recognition on dedicated datasets.
citing papers explorer
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Efficient RWKV-based Representation Learning for 3D Point Clouds
Introduces P-RWKV block and PointER self-supervised framework to adapt RWKV for efficient 3D point cloud representation learning.
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PestVL-Net: Enabling Multimodal Pest Learning via Fine-grained Vision-Language Interaction
PestVL-Net combines an RWKV visual backbone with saliency-guided window partitioning and MLLM-derived linguistic priors via multimodal chain-of-thought to enable fine-grained multimodal pest recognition on dedicated datasets.
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