[ad_1] Diffusion models have become the prevailing approach for generating videos. Yet, their dependence on large-scale web data, which varies in quality, frequently leads to outcomes lacking visual appeal and not aligning well with the provided textual prompts. Despite advancements in recent times,…

[ad_1] Transformer models are crucial in machine learning for language and vision processing tasks. Transformers, renowned for their effectiveness in sequential data handling, play a pivotal role in natural language processing and computer vision. They are designed to process input data in parallel,…

[ad_1] The use of diffusion models for interactive image generation is a burgeoning area of research. These models are lauded for creating high-quality images from various prompts and finding applications in digital art, virtual reality, and augmented reality. However, their real-time interaction capabilities…

[ad_1] Researchers from Alibaba, Zhejiang University, and Huazhong University of Science and Technology have come together and introduced a groundbreaking video synthesis model, I2VGen-XL, addressing key challenges in semantic accuracy, clarity, and spatio-temporal continuity. Video generation is often hindered by the scarcity of…

[ad_1] Although it would be helpful for applications like autonomous driving and mobile robotics, monocular estimation of metric depth in general situations has been difficult to achieve. Indoor and outdoor datasets have drastically different RGB and depth distributions, which presents a challenge. Another…

[ad_1] In response to the challenging task of generating realistic 3D human-object interactions (HOIs) guided by textual prompts, researchers from Northeastern University, Hangzhou Dianzi University, Stability AI, and Google Research have introduced an innovative solution called HOI-Diff. The intricacies of human-object interactions in…

[ad_1] LLMs have ushered in a new era of general-purpose vision systems, showcasing their prowess in processing visual inputs. This integration has led to the unification of diverse vision-language tasks through instruction tuning, marking a significant stride in the convergence of natural language…

[ad_1] The challenge of seamlessly translating textual prompts or spontaneous scribbles into intricate 3D multi-view wire art has long been a pursuit at the intersection of artificial intelligence and artistic expression. Traditional methods like ShadowArt and MVWA have focused on geometric optimization or…