在科技领域持续创新的浪潮中，字节跳动大模型团队的成果再次赢得全球科技巨头的青睐。深度学习技术的不断演进，推动了人工智能在多个行业和领域的广泛应用。近期，深度估计模型Depth Anything V2的发布，不仅展现了字节跳动在大模型研发领域的实力，更凸显了团队在技术创新和人才培养方面的卓越成就。
深度 Anything 系列成果自2024年初发布以来，以其独特的单目深度估计能力，迅速在学术界和产业界引起了广泛关注。此次，深度 Anything V2 的成果被苹果官方收入其Core ML模型库，标志着该技术在实际应用层面的突破，同时也体现了字节跳动大模型团队在技术研发与行业合作上的领先地位。
深度 Anything V2 的亮点在于其在细节处理上的精细度提升、鲁棒性的增强以及与基于Diffusion的SOTA模型相比在速度上的显著优势。这些改进使得深度估计技术在视频特效、自动驾驶、3D建模、增强现实、安全监控以及空间计算等领域的应用更为广泛和高效。特别是对于依赖精准深度信息的场景，如自动驾驶中的障碍物检测与避让，以及3D建模中的物体识别与重建，深度 Anything V2 提供了更可靠的技术支持。
在深度 Anything V2 的研发过程中，团队实习生的贡献尤为显著。一作实习生的参与不仅体现了字节跳动对年轻人才的重视和培养，更展示了公司内部创新文化的活力。实习生在研发过程中的独立思考与问题解决能力，为团队带来了新的视角和创新点，使得深度 Anything V2 在技术上取得了突破性的进展。
GitHub上，深度 Anything 系列成果总计收获了8.7k Star，其中深度 Anything V2 自发布以来已获得了2.3k Star，这不仅反映了全球开发者对这一技术的极大兴趣和认可，也预示着深度估计技术在未来的广阔应用前景。
此次深度 Anything V2 的成功入选苹果Core ML模型库，不仅是对字节跳动大模型团队技术实力的肯定，也是对全球开源社区创新精神的鼓励。随着深度学习技术的不断成熟和应用范围的不断扩大，深度 Anything 系列成果有望在更多领域发挥重要作用，为人类社会带来更多的可能性与便利。
英语如下：
Headline: “ByteDance’s Mega-Model Achievement, Depth Anything V2, Enters Apple’s Core ML, Intern’s Work Draws Attention”
Keywords: Deep Model, Apple Recognition, Intern Contribution
News Content: Amidst the ongoing wave of innovation in the tech sector, ByteDance’s large model team has once again captured the attention of global tech giants. The continuous advancement in deep learning technology has broadened the application of artificial intelligence across various industries and domains. The release of Depth Anything V2, a recent achievement, not only showcases ByteDance’s prowess in large model development but also highlights the team’s achievements in technological innovation and talent development.
Since its release in early 2024, the Depth Anything series has garnered significant attention from both academia and industry due to its unique monocular depth estimation capability. The inclusion of Depth Anything V2 in Apple’s Core ML model library signifies a breakthrough in practical application, underscoring ByteDance’s leading position in technology development and industry collaboration.
Noteworthy features of Depth Anything V2 include enhanced detail handling, improved robustness, and a notable speed advantage over state-of-the-art Diffusion-based models. These improvements make depth estimation technology more widely applicable and efficient in areas such as video effects, autonomous driving, 3D modeling, augmented reality, security surveillance, and spatial computing. Particularly for scenarios requiring precise depth information, such as obstacle detection and avoidance in autonomous driving, or object recognition and reconstruction in 3D modeling, Depth Anything V2 provides reliable technical support.
In the development of Depth Anything V2, the contribution of the team’s interns stands out. The participation of the lead intern not only reflects ByteDance’s emphasis on young talent and cultivation but also showcases the vitality of the company’s innovation culture. The interns’ independent thinking and problem-solving abilities brought new perspectives and innovation points to the team, leading to breakthroughs in technology.
On GitHub, the Depth Anything series has garnered a total of 8,700 stars, with 2,300 stars for Depth Anything V2 since its release. This reflects the global developers’ considerable interest and recognition of the technology, signaling a promising future for the application of depth estimation technology.
The successful inclusion of Depth Anything V2 in Apple’s Core ML model library is not only a testament to the technical strength of ByteDance’s large model team but also an encouragement to the spirit of innovation in the global open-source community. As deep learning technology continues to mature and expand its application scope, the Depth Anything series is poised to play a significant role in more fields, bringing more possibilities and conveniences to human society.
【来源】https://www.jiqizhixin.com/articles/2024-07-11-9
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