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20182026
most citedIntermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

37 citations · 75 across the 13 of their papers we have counts for

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20 papers · 1 filter

cs.CV2026

Dynamic-Robust Photometric-Semantic Reconstruction for Open-Vocabulary 3D Scene Understanding

Boyu Cai, Li Yang, Yan Xu +6

The integration of novel view synthesis (NVS) and open-vocabulary segmentation (OVS) has recently yielded powerful feed-forward 3D foundation models. However, their inherent relian…

cs.CV2026

Gaze-DETR: Top-Down Guidance Through Priority Maps for Infrared Weak-Small UAV Detection with DETR

Nian Liu, Yuxin Yang, Shubo Lin +6

Infrared small target detection (ISTD) remains challenging because tiny, low-contrast targets are easily overwhelmed by clutter, noise, or occlusion. Conventional single-frame and…

cs.CV2026

MI-DETR: A Strong Baseline for Moving Infrared Small Target Detection with Motion Integration

Nian Liu, Jin Gao, Shubo Lin +9

Detecting moving infrared small targets is challenging because tiny, low-contrast targets occupy few pixels and are easily obscured by dynamic backgrounds. Existing multi-frame met…

cs.CV2023

VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning

Ziyang Luo, Nian Liu, Wangbo Zhao +5

Salient object detection (SOD) and camouflaged object detection (COD) are related yet distinct binary mapping tasks. These tasks involve multiple modalities, sharing commonalities…

cs.CV2023

GP-NeRF: Generalized Perception NeRF for Context-Aware 3D Scene Understanding

Hao Li, Dingwen Zhang, Yalun Dai +5

Applying NeRF to downstream perception tasks for scene understanding and representation is becoming increasingly popular. Most existing methods treat semantic prediction as an addi…

cs.CV2023

VST++: Efficient and Stronger Visual Saliency Transformer

Nian Liu, Ziyang Luo, Ni Zhang +1

While previous CNN-based models have exhibited promising results for salient object detection (SOD), their ability to explore global long-range dependencies is restricted. Our prev…