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:2606. 06899v1 Announce Type: cross Abstract: Variations in illumination remain a major challenge for visual representation learning, as they induce substantial appearance changes both across and within environments.
By Lizhen Zhu, Charantej Reddy Pochimireddy, James Z Wang, Brad Wyble
Projector-camera (ProCams) systems achieve active scene perception and controllable appearance manipulation via structured illumination, serving as a core infrastructure for spatial augmented reality, projection mapping, and surface reflectance acquisition. Existing inverse-rendering methods for ProCams deliver high-fidelity results but rely on time-consuming per-scene optimization, while mainstream feed-forward 3D reconstruction models produce baked appearance that cannot adapt to spatially varying projector illumination.
arXiv:2607. 24110v1 Announce Type: cross Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception.
By Minchong Chen, Xiaoyun Yuan, Minyu Cao, Jianing Zhang, Jun Zhang, Shuyang Liu, Xiaokang Yang
arXiv:2502. 07531v5 Announce Type: replace-cross Abstract: Controllable image-to-video (I2V) generation transforms a reference image into a coherent video guided by user-specified control signals.
By Sixiao Zheng, Zimian Peng, Yanpeng Zhou, Yi Zhu, Hang Xu, Xiangru Huang, Yanwei Fu
arXiv:2608. 15972v1 Announce Type: cross Abstract: Synchronized camera and wireless measurements observe the same scene through different physical channels.
By Yubo Zhang, Yiyao Liu
Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cross-sensor misalignment caused by different optics, viewpoints, fields of view, and exposure timings hinders practical deployment.
arXiv:2606. 17615v1 Announce Type: cross Abstract: Estimating human proficiency from video is a key challenge for automated skill assessment, with applications in sports coaching, music pedagogy, surgical training, and workplace learning.
By Edoardo Bianchi, Antonio Liotta
arXiv:2608. 14702v1 Announce Type: cross Abstract: Film emulation reproduces the look of an analog film stock on a new digital photograph.
By Yitong Mu
arXiv:2606. 20559v1 Announce Type: cross Abstract: Egocentric video understanding is inherently limited by the narrow perspective of wearable cameras: a single viewpoint, a single modality, a single model cannot capture the full richness of human action.
By Wenhao Chi, Arkaprava Sinha, Dominick Reilly, Hieu Le, Srijan Das
arXiv:2607. 17790v1 Announce Type: cross Abstract: Egocentric devices, such as wearable front-facing cameras, provide a unique perspective for capturing the continuous interaction between a human viewer and the surrounding environment.
By Xiaozhong Lyu, Gen Li, Zhiyin Qian, Xucong Zhang, Marc Pollefeys, Siyu Tang
Low-light image enhancement (LLIE) methods involve tunable parameters that are typically fixed, often leading to performance degradation when applied across scenes. Manually selecting the best configuration, however, can be time-consuming and not always practical.