7 citations · 11 across the 4 of their papers we have counts for
7 papers
Identity Preserving Loss for Learned Image Compression
Jiuhong Xiao, Lavisha Aggarwal, Prithviraj Banerjee +2
Deep learning model inference on embedded devices is challenging due to the limited availability of computation resources. A popular alternative is to perform model inference on th…
OutfitTransformer: Learning Outfit Representations for Fashion Recommendation
Rohan Sarkar, Navaneeth Bodla, Mariya I. Vasileva +4
Learning an effective outfit-level representation is critical for predicting the compatibility of items in an outfit, and retrieving complementary items for a partial outfit. We pr…
Efficient Video Instance Segmentation via Tracklet Query and Proposal
Jialian Wu, Sudhir Yarram, Hui Liang +4
Video Instance Segmentation (VIS) aims to simultaneously classify, segment, and track multiple object instances in videos. Recent clip-level VIS takes a short video clip as input e…
Energy-Based Learning for Scene Graph Generation
Mohammed Suhail, Abhay Mittal, Behjat Siddiquie +4
Traditional scene graph generation methods are trained using cross-entropy losses that treat objects and relationships as independent entities. Such a formulation, however, ignores…
GAN-Control: Explicitly Controllable GANs
Alon Shoshan, Nadav Bhonker, Igor Kviatkovsky +1
We present a framework for training GANs with explicit control over generated images. We are able to control the generated image by settings exact attributes such as age, pose, exp…
From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding
Igor Kviatkovsky, Nadav Bhonker, Gerard Medioni
We present a method for synthesizing naturally looking images of multiple people interacting in a specific scenario. These images benefit from the advantages of synthetic data: bei…