123 citations · 171 across the 8 of their papers we have counts for
5 papers · 1 filter
Language-Guided Image Tokenization for Generation
Kaiwen Zha, Lijun Yu, Alireza Fathi +4
Image tokenization, the process of transforming raw image pixels into a compact low-dimensional latent representation, has proven crucial for scalable and efficient image generatio…
Unsupervised Image Transformation Learning via Generative Adversarial Networks
Kaiwen Zha, Yujun Shen, Bolei Zhou
In this work, we study the image transformation problem, which targets at learning the underlying transformations (e.g., the transition of seasons) from a collection of unlabeled i…
Complex Sequential Understanding through the Awareness of Spatial and Temporal Concepts
Bo Pang, Kaiwen Zha, Hanwen Cao +3
Understanding sequential information is a fundamental task for artificial intelligence. Current neural networks attempt to learn spatial and temporal information as a whole, limite…
Deep RNN Framework for Visual Sequential Applications
Bo Pang, Kaiwen Zha, Hanwen Cao +2
Extracting temporal and representation features efficiently plays a pivotal role in understanding visual sequence information. To deal with this, we propose a new recurrent neural…
Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model
Bo Pang, Kaiwen Zha, Cewu Lu
We introduce the first benchmark for a new problem --- recognizing human action adverbs (HAA): "Adverbs Describing Human Actions" (ADHA). This is the first step for computer vision…