activity
20162023
most citedRecovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning

22 citations · 30 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV20231 cited

How you feelin'? Learning Emotions and Mental States in Movie Scenes

Dhruv Srivastava, Aditya Kumar Singh, Makarand Tapaswi

Movie story analysis requires understanding characters' emotions and mental states. Towards this goal, we formulate emotion understanding as predicting a diverse and multi-label se…

cs.CV20221 cited

Unsupervised Audio-Visual Lecture Segmentation

Darshan Singh S, Anchit Gupta, C. V. Jawahar +1

Over the last decade, online lecture videos have become increasingly popular and have experienced a meteoric rise during the pandemic. However, video-language research has primaril…

cs.CV2022

Learning from Unlabeled 3D Environments for Vision-and-Language Navigation

Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi +2

In vision-and-language navigation (VLN), an embodied agent is required to navigate in realistic 3D environments following natural language instructions. One major bottleneck for ex…

cs.CV20164 cited

Relaxed Earth Mover's Distances for Chain- and Tree-connected Spaces and their use as a Loss Function in Deep Learning

Manuel Martinez, Monica Haurilet, Ziad Al-Halah +2

The Earth Mover's Distance (EMD) computes the optimal cost of transforming one distribution into another, given a known transport metric between them. In deep learning, the EMD los…

cs.CV201622 cited

Recovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning

Ziad Al-Halah, Makarand Tapaswi, Rainer Stiefelhagen

Collecting training images for all visual categories is not only expensive but also impractical. Zero-shot learning (ZSL), especially using attributes, offers a pragmatic solution…