1.1k citations · 1.2k across the 24 of their papers we have counts for
12 papers · 1 filter
See, Say, and Segment: Teaching LMMs to Overcome False Premises
Tsung-Han Wu, Giscard Biamby, David Chan +5
Current open-source Large Multimodal Models (LMMs) excel at tasks such as open-vocabulary language grounding and segmentation but can suffer under false premises when queries imply…
CLAIR: Evaluating Image Captions with Large Language Models
David Chan, Suzanne Petryk, Joseph E. Gonzalez +2
The evaluation of machine-generated image captions poses an interesting yet persistent challenge. Effective evaluation measures must consider numerous dimensions of similarity, inc…
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data
Vladislav Lialin, Stephen Rawls, David Chan +3
Scaling up weakly-supervised datasets has shown to be highly effective in the image-text domain and has contributed to most of the recent state-of-the-art computer vision and multi…
IC3: Image Captioning by Committee Consensus
David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan +2
If you ask a human to describe an image, they might do so in a thousand different ways. Traditionally, image captioning models are trained to generate a single "best" (most like a…
LAVA: Language Audio Vision Alignment for Contrastive Video Pre-Training
Sumanth Gurram, Andy Fang, David Chan +1
Generating representations of video data is of key importance in advancing the field of machine perception. Most current techniques rely on hand-annotated data, which can be diffic…
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics
David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan +3
While there have been significant gains in the field of automated video description, the generalization performance of automated description models to novel domains remains a major…
Misinformation Detection in Social Media Video Posts
Kehan Wang, David Chan, Seth Z. Zhao +2
With the growing adoption of short-form video by social media platforms, reducing the spread of misinformation through video posts has become a critical challenge for social media…
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery
Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding +2
Urban areas consume over two-thirds of the world's energy and account for more than 70 percent of global CO2 emissions. As stated in IPCC's Global Warming of 1.5C report, achieving…
Active Learning for Video Description With Cluster-Regularized Ensemble Ranking
David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross +1
Automatic video captioning aims to train models to generate text descriptions for all segments in a video, however, the most effective approaches require large amounts of manual an…
Leveraging Class Similarity to Improve Deep Neural Network Robustness
Pooran Singh Negi, David chan, Mohammad Mahoor
Traditionally artificial neural networks (ANNs) are trained by minimizing the cross-entropy between a provided groundtruth delta distribution (encoded as one-hot vector) and the AN…
Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics
Biye Jiang, David M. Chan, Tianhao Zhang +1
The internal states of most deep neural networks are difficult to interpret, which makes diagnosis and debugging during training challenging. Activation maximization methods are wi…
Facial Expression Recognition from World Wild Web
Ali Mollahosseini, Behzad Hassani, Michelle J. Salvador +3
Recognizing facial expression in a wild setting has remained a challenging task in computer vision. The World Wide Web is a good source of facial images which most of them are capt…