630 citations · 1.4k across the 7 of their papers we have counts for
8 papers · 1 filter
Toward Transformer-Based Object Detection
Josh Beal, Eric Kim, Eric Tzeng +3
Transformers have become the dominant model in natural language processing, owing to their ability to pretrain on massive amounts of data, then transfer to smaller, more specific t…
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition
Mohammad Reza Loghmani, Luca Robbiano, Mirco Planamente +3
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distribution…
Revisiting Few-shot Activity Detection with Class Similarity Control
Huijuan Xu, Ximeng Sun, Eric Tzeng +3
Many interesting events in the real world are rare making preannotated machine learning ready videos a rarity in consequence. Thus, temporal activity detection models that are able…
Learning a Unified Embedding for Visual Search at Pinterest
Andrew Zhai, Hao-Yu Wu, Eric Tzeng +2
At Pinterest, we utilize image embeddings throughout our search and recommendation systems to help our users navigate through visual content by powering experiences like browsing o…
SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection
Eric Tzeng, Kaylee Burns, Kate Saenko +1
Domain adaptation of visual detectors is a critical challenge, yet existing methods have overlooked pixel appearance transformations, focusing instead on bootstrapping and/or domai…
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman, Eric Tzeng, Taesung Park +5
Domain adaptation is critical for success in new, unseen environments. Adversarial adaptation models applied in feature spaces discover domain invariant representations, but are di…