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Found 10 papers, 3 papers with code
Modular Visual Question Answering via Code Generation
We present a framework that formulates visual question answering as modular code generation.
Learning and Verification of Task Structure in Instructional Videos
We introduce a new pre-trained video model, VideoTaskformer, focused on representing the semantics and structure of instructional videos.
TL;DW? Summarizing Instructional Videos with Task Relevance & Cross-Modal Saliency
In this work, we focus on summarizing instructional videos, an under-explored area of video summarization.
Multi-Person 3D Motion Prediction with Multi-Range Transformers
Thus, instead of predicting each human pose trajectory in isolation, we introduce a Multi-Range Transformers model which contains of a local-range encoder for individual motion and a global-range encoder for social interactions.
CLIP-It! Language-Guided Video Summarization
A generic video summary is an abridged version of a video that conveys the whole story and features the most important scenes.
Strumming to the Beat: Audio-Conditioned Contrastive Video Textures
We learn representations for video frames and frame-to-frame transition probabilities by fitting a video-specific model trained using contrastive learning.
Contrastive Video Textures
By randomly traversing edges with high transition probabilities, we generate diverse temporally smooth videos with novel sequences and transitions.
Seeing the Un-Scene: Learning Amodal Semantic Maps for Room Navigation
We also demonstrate that reducing the task of room navigation to point navigation improves the performance further.
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering
Given a question-image pair, deep network techniques have been employed to successively reduce the large set of facts until one of the two entities of the final remaining fact is predicted as the answer.
Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual Question Answering
Question answering is an important task for autonomous agents and virtual assistants alike and was shown to support the disabled in efficiently navigating an overwhelming environment.
