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Found 6 papers, 3 papers with code
Learning to Embed Multi-Modal Contexts for Situated Conversational Agents
The Situated Interactive Multi-Modal Conversations (SIMMC) 2. 0 aims to create virtual shopping assistants that can accept complex multi-modal inputs, i. e. visual appearances of objects and user utterances.
Ranked #2 on
Response Generation
on SIMMC2.0
StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On
Given a clothing image and a person image, an image-based virtual try-on aims to generate a customized image that appears natural and accurately reflects the characteristics of the clothing image.
Learning to Generate Semantic Layouts for Higher Text-Image Correspondence in Text-to-Image Synthesis
Our experiments reveal that we can guide text-to-image generation models to be aware of the semantics of different image regions, by training the model to generate semantic labels for each pixel.
iColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer
It is essential for point-interactive colorization methods to appropriately propagate user-provided colors (i. e., user hints) in the entire image to obtain a reasonably colorized image with minimal user effort.
Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images
For a human expert, the depth adjustment procedure is a sequence of iterative decision making.
Generative Guiding Block: Synthesizing Realistic Looking Variants Capable of Even Large Change Demands
Generating realistic looking images with large variations (e. g., large spatial deformations and large pose change), however, is very challenging.
