Paper Submissions

We invite 4-page abstracts in ICCV format (including references) of new or previously published work addressing the topics outlined below. (For the previously published works re-formatting is not necessary.) We will make the accepted submissions available on our website as non-archival reports, and will also allow for peer-reviewed novel submissions to appear in the ICCV workshop proceedings. The accepted works will be presented in the poster session and some will be selected for oral presentation.

CMT Website: https://cmt3.research.microsoft.com/ICCV2019CLVL

Format:  The submission should follow the ICCV 2019 submission instructions. 

• • Novel problems in vision and language

  • Learning to solve non-visual tasks using visual cues

  • Language guided visual understanding (objects, relationships)

  • Visual dialog and question answering by visual verification

  • Visual question generation

  • Visually grounded conversation

  • Visual sense disambiguation

  • Deep learning methods for vision and language

  • Visual reasoning on language problems

  • Text-to-image generation

  • Language based visual abstraction

  • Text as weak labels for image or video classification.

  • Image/Video Annotation and natural language description generation

  • Transfer learning for vision and language

  • Jointly learn to parse and perceive (text+image, text+video)

  • Multimodal clustering and word sense disambiguation

  • Unstructured text search for visual content

  • Visually grounded language acquisition and understanding

  • Referring expression comprehension

  • Language-based image and video search/retrieval

  • Linguistic descriptions of spatial relations

  • Auto-illustration

  • Natural language grounding & learning by watching  

  • Learning knowledge from the web

  • Language as a mechanism to structure and reason about visual perception

  • Language as a learning bias to aid vision in both machines and humans

  • Dialog as means of sharing knowledge about visual perception

  • Stories as means of abstraction

  • Understanding the relationship between language and vision in humans

  • Humanistic, subjective, or expressive vision-to-language

  • Visual storytelling

  • Generating Audio Descriptions for movies

  • Multi-sentence descriptions for images and videos

  • Visual question answering for video

  • Visual fill-in-the blank tasks

  • Language as supervision for video understanding

  • Using dialogs and/or audio for video understanding

  • Understanding videos and plots

  • Limitations of existing vision and language datasets

  • Limitations of existing vision and language approaches