arXiv:2501. 13692v2 Announce Type: replace-cross Abstract: Diffusion models have recently unlocked new possibilities in editing images of real-world objects.
By Potito Aghilar, Vito Walter Anelli, Michelantonio Trizio, Eugenio Di Sciascio, Tommaso Di Noia
arXiv:2606. 02242v1 Announce Type: cross Abstract: The joint optimization of image-based (I2I) and text-based (T2I) person re-identification (ReID) is hindered by modality discrepancies and conflicting training objectives, leading to suboptimal shared representations.
By Karina Kvanchiani, Timur Mamedov
The paper introduces a new framework for unsupervised visible‑infrared person re‑identification that leverages modality‑unified prototypes. By contrasting with prototypes that unify both modalities, the method jointly optimizes similarity within and across modalities, improving modality invariance. A self‑distillation step refines instance‑prototype relationships using a steady teacher, resulting in a simple yet effective model validated on standard VI‑ReID benchmarks.
By Menglin Wang, Xiaojin Gong
The joint optimization of image-based (I2I) and text-based (T2I) person re-identification (ReID) is hindered by modality discrepancies and conflicting training objectives, leading to suboptimal shared representations. While I2I ReID focuses on identity-level invariance across images of the same person, T2I ReID is driven by instance-specific textual descriptions tied to unique visual traits.
arXiv:2607. 17157v1 Announce Type: cross Abstract: Multi-object tracking (MOT) aims to localize multiple objects in videos while preserving their identities over time.
By Yanrong Qin, Xiaoyan Cao, Yao Yao
arXiv:2609.36894v1 Announce Type: new
Abstract: As a fundamental image processing task, object Re-Identification (ReID) aims to retrieve objects across non-overlapping cameras. Recently, with the dev...
By Yingquan Wang, Pingping Zhang, Dong Wang, Huchuan Lu
arXiv:2609.14419v1 Announce Type: cross
Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chan...
By Leon Fernando, C Dombawala, P. Hettigoda, Vanodhya G. Warnasooriya, Ishara Neranjana, Rashmika Nawaratne
As a fundamental image processing task, object Re-Identification (ReID) aims to retrieve objects across non-overlapping cameras. Recently, with the development of deep learning, significant advancemen...
arXiv:2609.36560v1 Announce Type: cross
Abstract: Object re-identification (ReID) faces a recurring challenge: different identities can share highly similar global appearances, while the cues that di...
By Zhiqi Li, Xiaowei Zhou, Zeyuan Sun, Feng Gao, Junyu Dong
Personalizing text-to-image diffusion models to render several specific subjects in a coherent image remains challenging: the model must preserve each subject's identity while keeping the scene spatially and visually coherent. Methods that fuse independently trained concept adapters in a shared weight space (via federated averaging, gradient fusion, or orthogonality constraints) suffer from identity confusion and style bleeding and require joint retraining.
arXiv:2609.39335v1 Announce Type: new
Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing met...
By Zijing Qin, Jun Zhou, Ruicheng Zhang, Jiaqi Hou, Zunnan Xu, Ronghui Li, Zhenyu Xie, Xiu Li
arXiv:2606. 07233v1 Announce Type: cross Abstract: LiDAR-based 3D Multi-Object Tracking (MOT) typically relies solely on geometric information, which is often insufficient to distinguish between targets during prolonged occlusions or in crowded human-populated environments.
By Eduardo Borges, Lu\'is Garrote, Urbano J. Nunes