arXiv Computer Vision

Optimizing Multi-Modality Trackers via Significance-Regularized Tuning

arXiv Computer Vision
2d ago

MAETrack: Unleashing the Potential of Pretrained Geometric Priors for 3D Single Object Tracking

MAETrack introduces a lightweight framework to adapt pretrained masked autoencoder (MAE) representations for 3D single object tracking (SOT). It uses Layer‑Selective Initialization (LSI) to keep shallow geometric layers from the pre‑training while re‑initializing deeper layers, and Geometric Residual Gating (GRG) to emphasize salient regions in BEV features before template‑search fusion. Experiments on standard 3D SOT benchmarks show consistent improvements over vanilla fine‑tuning with minimal computational cost.

By Sifan Zhou, Qiwei Wang, Linyue Tan, Ziyu Liu, Ziyu Zhao, Xiaobo Lu
arXiv AI
Jul 16

Fre-Res: Frequency-Residual Video Token Compression for Efficient Video MLLMs

arXiv:2605. 16366v2 Announce Type: replace-cross Abstract: Video MLLMs face a persistent tension between spatial fidelity and temporal coverage: preserving fine-grained visual details requires many spatial tokens, while capturing short-lived events requires dense temporal sampling.

By Yigui Feng (The College of Computer Science, National University of Defense Technology, Changsha, Hunan, China), Qinglin Wang (The College of Computer Science, National University of Defense Technology, Changsha, Hunan, China), Yang Liu (The Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, Guangdong, China), Jie Liu (The College of Computer Science, National University of Defense Technology, Changsha, Hunan, China)
Hugging Face Trending Papers
Aug 13

P2Fusion: Prompt-based Progressive Infrared-Visible Image Fusion via Dual-Prior Distillation

Infrared-visible image fusion (IVIF) is pivotal for multimodal perception, yet reconciling the inherent information disparity between thermal and textural features remains a fundamental challenge. Existing prior-guided methods often rely on static constraints that induce optimization conflicts or utilize extrinsic semantic priors from large-scale foundation models (e.

arXiv Computer Vision
Aug 24

Prompt2Effect: Training-Free Image-to-Video Model Specialization via LoRA Generation

arXiv:2606.13971v3 Announce Type: replace Abstract: While personalizing Image-to-Video (I2V) diffusion models with specific visual effects is increasingly demanded for high-end generation, current pr...

By Xiaomeng Yang, Yanyu Li, Gordon Guocheng Qian, Ivan Skorokhodov, Viacheslav Ivanov, Avalon Vinella, Xuan Zhang, Yanzhi Wang, Sergey Tulyakov, Anil Kag