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20232026
most citedPrivacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

7 citations · 17 across the 51 of their papers we have counts for

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12 papers · 1 filter

cs.CV2025

Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression

Xiang Liu, Yimin Zhou, Jinxiang Wang +9

The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms…

cs.CV2025

Closing the Safety Gap: Surgical Concept Erasure in Visual Autoregressive Models

Xinhao Zhong, Yimin Zhou, Zhiqi Zhang +6

The rapid progress of visual autoregressive (VAR) models has brought new opportunities for text-to-image generation, but also heightened safety concerns. Existing concept erasure t…

cs.CV2025

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization

Yixiang Qiu, Yanhan Liu, Hongyao Yu +4

The growing complexity of Deep Neural Networks (DNNs) has led to the adoption of Split Inference (SI), a collaborative paradigm that partitions computation between edge devices and…

cs.CV2025

HLFormer: Enhancing Partially Relevant Video Retrieval with Hyperbolic Learning

Jun Li, Jinpeng Wang, Chaolei Tan +6

Partially Relevant Video Retrieval (PRVR) addresses the critical challenge of matching untrimmed videos with text queries describing only partial content. Existing methods suffer f…

cs.IT2025

EDPC: Accelerating Lossless Compression via Lightweight Probability Models and Decoupled Parallel Dataflow

Zeyi Lu, Xiaoxiao Ma, Yujun Huang +4

The explosive growth of multi-source multimedia data has significantly increased the demands for transmission and storage, placing substantial pressure on bandwidth and storage inf…

cs.CV2025

ICAS: Detecting Training Data from Autoregressive Image Generative Models

Hongyao Yu, Yixiang Qiu, Yiheng Yang +6

Autoregressive image generation has witnessed rapid advancements, with prominent models such as scale-wise visual auto-regression pushing the boundaries of visual synthesis. Howeve…