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cs.CV2025

TSLA: A Task-Specific Learning Adaptation for Semantic Segmentation on Autonomous Vehicles Platform

Jun Liu, Zhenglun Kong, Pu Zhao +9

Autonomous driving platforms encounter diverse driving scenarios, each with varying hardware resources and precision requirements. Given the computational limitations of embedded d…

cs.CV2025

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation

Xiaomeng Yang, Lei Lu, Qihui Fan +5

Diffusion models have demonstrated exceptional capabilities in generating high-fidelity images. However, their iterative denoising process results in significant computational over…

cs.CV2025

QuartDepth: Post-Training Quantization for Real-Time Depth Estimation on the Edge

Xuan Shen, Weize Ma, Jing Liu +9

Monocular Depth Estimation (MDE) has emerged as a pivotal task in computer vision, supporting numerous real-world applications. However, deploying accurate depth estimation models…

cs.CV2024

Fast and Memory-Efficient Video Diffusion Using Streamlined Inference

Zheng Zhan, Yushu Wu, Yifan Gong +7

The rapid progress in artificial intelligence-generated content (AIGC), especially with diffusion models, has significantly advanced development of high-quality video generation. H…

cs.CV2024

InstructGIE: Towards Generalizable Image Editing

Zichong Meng, Changdi Yang, Jun Liu +3

Recent advances in image editing have been driven by the development of denoising diffusion models, marking a significant leap forward in this field. Despite these advances, the ge…

cs.CV2024

DiffClass: Diffusion-Based Class Incremental Learning

Zichong Meng, Jie Zhang, Changdi Yang +3

Class Incremental Learning (CIL) is challenging due to catastrophic forgetting. On top of that, Exemplar-free Class Incremental Learning is even more challenging due to forbidden a…