Zobrazeno 1 - 10
of 27 199
pro vyhledávání: '"large scale dataset"'
Autor:
Li, Zejian, Meng, Chenye, Li, Yize, Yang, Ling, Zhang, Shengyuan, Ma, Jiarui, Li, Jiayi, Yang, Guang, Yang, Changyuan, Yang, Zhiyuan, Chang, Jinxiong, Sun, Lingyun
Recent advances in text-to-image (T2I) generation have shown remarkable success in producing high-quality images from text. However, existing T2I models show decayed performance in compositional image generation involving multiple objects and intrica
Externí odkaz:
http://arxiv.org/abs/2412.08580
Retractions play a vital role in maintaining scientific integrity, yet systematic studies of retractions in computer science and other STEM fields remain scarce. We present WithdrarXiv, the first large-scale dataset of withdrawn papers from arXiv, co
Externí odkaz:
http://arxiv.org/abs/2412.03775
Autor:
Chu, Zedong, Xiong, Feng, Liu, Meiduo, Zhang, Jinzhi, Shao, Mingqi, Sun, Zhaoxu, Wang, Di, Xu, Mu
With the rapid evolution of 3D generation algorithms, the cost of producing 3D humanoid character models has plummeted, yet the field is impeded by the lack of a comprehensive dataset for automatic rigging, which is a pivotal step in character animat
Externí odkaz:
http://arxiv.org/abs/2412.02317
Autor:
Yamagishi, Yosuke, Nakamura, Yuta, Kikuchi, Tomohiro, Sonoda, Yuki, Hirakawa, Hiroshi, Kano, Shintaro, Nakamura, Satoshi, Hanaoka, Shouhei, Yoshikawa, Takeharu, Abe, Osamu
Background: Recent advances in large language models highlight the need for high-quality multilingual medical datasets. While Japan leads globally in CT scanner deployment and utilization, the lack of large-scale Japanese radiology datasets has hinde
Externí odkaz:
http://arxiv.org/abs/2412.15907
Alignment-free RGB-Thermal (RGB-T) salient object detection (SOD) aims to achieve robust performance in complex scenes by directly leveraging the complementary information from unaligned visible-thermal image pairs, without requiring manual alignment
Externí odkaz:
http://arxiv.org/abs/2412.14576
Autor:
Wu, Yongliang, Zhu, Wenbo, Cao, Jiawang, Lu, Yi, Li, Bozheng, Chi, Weiheng, Qiu, Zihan, Su, Lirian, Zheng, Haolin, Wu, Jay, Yang, Xu
The demand for producing short-form videos for sharing on social media platforms has experienced significant growth in recent times. Despite notable advancements in the fields of video summarization and highlight detection, which can create partially
Externí odkaz:
http://arxiv.org/abs/2412.08879
Autor:
Pal, Anisha, Kruk, Julia, Phute, Mansi, Bhattaram, Manognya, Yang, Diyi, Chau, Duen Horng, Hoffman, Judy
Text-to-image diffusion models have impactful applications in art, design, and entertainment, yet these technologies also pose significant risks by enabling the creation and dissemination of misinformation. Although recent advancements have produced
Externí odkaz:
http://arxiv.org/abs/2411.07472
Dataset distillation or condensation refers to compressing a large-scale dataset into a much smaller one, enabling models trained on this synthetic dataset to generalize effectively on real data. Tackling this challenge, as defined, relies on a bi-le
Externí odkaz:
http://arxiv.org/abs/2410.07579
Autor:
Xiao, Lingao, He, Yang
In ImageNet-condensation, the storage for auxiliary soft labels exceeds that of the condensed dataset by over 30 times. However, are large-scale soft labels necessary for large-scale dataset distillation? In this paper, we first discover that the hig
Externí odkaz:
http://arxiv.org/abs/2410.15919
Autor:
Ma, Qi, Li, Yue, Ren, Bin, Sebe, Nicu, Konukoglu, Ender, Gevers, Theo, Van Gool, Luc, Paudel, Danda Pani
3D Gaussian Splatting (3DGS) has become the de facto method of 3D representation in many vision tasks. This calls for the 3D understanding directly in this representation space. To facilitate the research in this direction, we first build a large-sca
Externí odkaz:
http://arxiv.org/abs/2408.10906