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Found 7 papers, 4 papers with code
Affective Faces for Goal-Driven Dyadic Communication
We introduce a video framework for modeling the association between verbal and non-verbal communication during dyadic conversation.
FLEX: Full-Body Grasping Without Full-Body Grasps
Towards this goal, we address the task of generating a virtual human -- hands and full body -- grasping everyday objects.
Landscape Learning for Neural Network Inversion
Many machine learning methods operate by inverting a neural network at inference time, which has become a popular technique for solving inverse problems in computer vision, robotics, and graphics.
SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency
Recent research in Visual Question Answering (VQA) has revealed state-of-the-art models to be inconsistent in their understanding of the world -- they answer seemingly difficult questions requiring reasoning correctly but get simpler associated sub-questions wrong.
Feel The Music: Automatically Generating A Dance For An Input Song
We encode intuitive, flexible heuristics for what a 'good' dance is: the structure of the dance should align with the structure of the music.
SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions
We quantify the extent to which this phenomenon occurs by creating a new Reasoning split of the VQA dataset and collecting VQA-introspect, a new dataset1 which consists of 238K new perception questions which serve as sub questions corresponding to the set of perceptual tasks needed to effectively answer the complex reasoning questions in the Reasoning split.
Trick or TReAT: Thematic Reinforcement for Artistic Typography
An approach to make text visually appealing and memorable is semantic reinforcement - the use of visual cues alluding to the context or theme in which the word is being used to reinforce the message (e. g., Google Doodles).
