In the rapidly advancing field of multi-modal machine learning (MMML), the convergence of
multiple data modalities has the potential to reshape various applications. This paper …

Advances in multimodal machine learning help artificial intelligence to resemble human
intellect more closely, which perceives the world from multiple modalities. We surveyed state …

The artistic style within a painting is the means of expression, which includes not only the
painting material, colors, and brushstrokes, but also the high-level attributes, including …

Abstract Contrastive Language-Image Pre-training (CLIP) has been the cornerstone for zero-
shot classification, text-image retrieval, and text-image generation by aligning image and …

We propose a novel unsupervised backlit image enhancement method, abbreviated as CLIP-
LIT, by exploring the potential of Contrastive Language-Image Pre-Training (CLIP) for pixel …

By decomposing the image formation process into a sequential application of denoising
autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image …

We present a method for zero-shot, text-driven editing of natural images and videos. Given
an image or a video and a text prompt, our goal is to edit the appearance of existing objects …

We combine neural rendering with multi-modal image and text representations to synthesize
diverse 3D objects solely from natural language descriptions. Our method, Dream Fields …

3D avatar creation plays a crucial role in the digital age. However, the whole production
process is prohibitively time-consuming and labor-intensive. To democratize this technology …

We introduce MotionCLIP, a 3D human motion auto-encoder featuring a latent embedding
that is disentangled, well behaved, and supports highly semantic textual descriptions …