123 citations · 171 across the 8 of their papers we have counts for
8 papers
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…
Rank-N-Contrast: Learning Continuous Representations for Regression
Kaiwen Zha, Peng Cao, Jeany Son +2
Deep regression models typically learn in an end-to-end fashion without explicitly emphasizing a regression-aware representation. Consequently, the learned representations exhibit…
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
Hao He, Kaiwen Zha, Dina Katabi
Indiscriminate data poisoning attacks are quite effective against supervised learning. However, not much is known about their impact on unsupervised contrastive learning (CL). This…
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…
Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen +2
Real-world data often exhibit imbalanced distributions, where certain target values have significantly fewer observations. Existing techniques for dealing with imbalanced data focu…
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…