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cs.CV2026

CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception

Liupeng Li, Haoqian Kang, Zhenyu Lu +4

High-resolution (HR) image perception presents a key bottleneck for multimodal large language models (MLLMs). While visual search offers a promising solution, existing methods stru…

cs.CV2026

SegCompass: Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning Segmentation

Zhenyu Lu, Liupeng Li, Jinpeng Wang +4

While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reasoning to visual perception. Cur…

cs.CV2025

CASL: Curvature-Augmented Self-supervised Learning for 3D Anomaly Detection

Yaohua Zha, Xue Yuerong, Chunlin Fan +4

Deep learning-based 3D anomaly detection methods have demonstrated significant potential in industrial manufacturing. However, many approaches are specifically designed for anomaly…

cs.CV2025

Point Cloud Mixture-of-Domain-Experts Model for 3D Self-supervised Learning

Yaohua Zha, Tao Dai, Hang Guo +4

Point clouds, as a primary representation of 3D data, can be categorized into scene domain point clouds and object domain point clouds. Point cloud self-supervised learning (SSL) h…

cs.CV2025

PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter

Yaohua Zha, Yanzi Wang, Hang Guo +7

Applying pre-trained models to assist point cloud understanding has recently become a mainstream paradigm in 3D perception. However, existing application strategies are straightfor…