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20212026
most citedSAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation

85 citations · 259 across the 105 of their papers we have counts for

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Showing 2025 · cs.CVShow all

24 papers · 2 filters

cs.CV2025

FakeRadar: Probing Forgery Outliers to Detect Unknown Deepfake Videos

Zhaolun Li, Jichang Li, Yinqi Cai +4

In this paper, we propose FakeRadar, a novel deepfake video detection framework designed to address the challenges of cross-domain generalization in real-world scenarios. Existing…

cs.CV2025

ContextDrag: Precise Drag-Based Image Editing via Context-Preserving Token Injection and Position-Aligned Attention

Huiguo He, Pengyu Yan, Ziqi Yi +6

Drag-based image editing enables intuitive visual manipulation through point-based drag operations. Existing methods mainly rely on diffusion inversion or pixel-space warping with…

cs.CV2025

Dual-domain Adaptation Networks for Realistic Image Super-resolution

Chaowei Fang, Bolin Fu, De Cheng +2

Realistic image super-resolution (SR) focuses on transforming real-world low-resolution (LR) images into high-resolution (HR) ones, handling more complex degradation patterns than…

cs.CV2025

LaneDiffusion: Improving Centerline Graph Learning via Prior Injected BEV Feature Generation

Zijie Wang, Weiming Zhang, Wei Zhang +4

Centerline graphs, crucial for path planning in autonomous driving, are traditionally learned using deterministic methods. However, these methods often lack spatial reasoning and s…

cs.CV2025

VLDrive: Vision-Augmented Lightweight MLLMs for Efficient Language-grounded Autonomous Driving

Ruifei Zhang, Wei Zhang, Xiao Tan +4

Recent advancements in language-grounded autonomous driving have been significantly promoted by the sophisticated cognition and reasoning capabilities of large language models (LLM…

cs.CV2025

AdaDrive: Self-Adaptive Slow-Fast System for Language-Grounded Autonomous Driving

Ruifei Zhang, Junlin Xie, Wei Zhang +4

Effectively integrating Large Language Models (LLMs) into autonomous driving requires a balance between leveraging high-level reasoning and maintaining real-time efficiency. Existi…