activity
20182026
most citedArgoverse: 3D Tracking and Forecasting with Rich Maps

157 citations · 172 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Infinite Gaze Generation for Videos with Autoregressive Diffusion

Jenna Kang, Colin Groth, Tong Wu +4

Predicting human gaze in video is fundamental to advancing scene understanding and multimodal interaction. While traditional saliency maps provide spatial probability distributions…

cs.CV2025

GeneVA: A Dataset of Human Annotations for Generative Text to Video Artifacts

Jenna Kang, Maria Silva, Patsorn Sangkloy +3

Recent advances in probabilistic generative models have extended capabilities from static image synthesis to text-driven video generation. However, the inherent randomness of their…

cs.CV2025

Cost-Aware Routing for Efficient Text-To-Image Generation

Qinchan Li, Kenneth Chen, Changyue Su +3

Diffusion models are well known for their ability to generate a high-fidelity image for an input prompt through an iterative denoising process. Unfortunately, the high fidelity als…

cs.CV2019157 cited

Argoverse: 3D Tracking and Forecasting with Rich Maps

Ming-Fang Chang, John Lambert, Patsorn Sangkloy +8

We present Argoverse -- two datasets designed to support autonomous vehicle machine learning tasks such as 3D tracking and motion forecasting. Argoverse was collected by a fleet of…

cs.LG20191 cited

Kernel Mean Matching for Content Addressability of GANs

Wittawat Jitkrittum, Patsorn Sangkloy, Muhammad Waleed Gondal +3

We propose a novel procedure which adds "content-addressability" to any given unconditional implicit model e.g., a generative adversarial network (GAN). The procedure allows users…

stat.ML2018

Informative Features for Model Comparison

Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy +3

Given two candidate models, and a set of target observations, we address the problem of measuring the relative goodness of fit of the two models. We propose two new statistical tes…