185 citations · 326 across the 41 of their papers we have counts for
10 papers · 2 filters
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning
Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed +4
We introduce Patch Aligned Contrastive Learning (PACL), a modified compatibility function for CLIP's contrastive loss, intending to train an alignment between the patch tokens of t…
CNeRV: Content-adaptive Neural Representation for Visual Data
Hao Chen, Matt Gwilliam, Bo He +2
Compression and reconstruction of visual data have been widely studied in the computer vision community, even before the popularization of deep learning. More recently, some have u…
: Backward-compatible Training with Basis Transformation
Yifei Zhou, Zilu Li, Abhinav Shrivastava +4
Modern retrieval system often requires recomputing the representation of every piece of data in the gallery when updating to a better representation model. This process is known as…
Diversified Dynamic Routing for Vision Tasks
Botos Csaba, Adel Bibi, Yanwei Li +2
Deep learning models for vision tasks are trained on large datasets under the assumption that there exists a universal representation that can be used to make predictions for all s…
Raising the Bar on the Evaluation of Out-of-Distribution Detection
Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen +4
In image classification, a lot of development has happened in detecting out-of-distribution (OoD) data. However, most OoD detection methods are evaluated on a standard set of datas…
Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation
Kevin Musgrave, Serge Belongie, Ser-Nam Lim
Changes to hyperparameters can have a dramatic effect on model accuracy. Thus, the tuning of hyperparameters plays an important role in optimizing machine-learning models. An integ…
Sample-dependent Adaptive Temperature Scaling for Improved Calibration
Tom Joy, Francesco Pinto, Ser-Nam Lim +2
It is now well known that neural networks can be wrong with high confidence in their predictions, leading to poor calibration. The most common post-hoc approach to compensate for t…
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions
Yongming Rao, Wenliang Zhao, Yansong Tang +3
Recent progress in vision Transformers exhibits great success in various tasks driven by the new spatial modeling mechanism based on dot-product self-attention. In this paper, we s…
VRAG: Region Attention Graphs for Content-Based Video Retrieval
Kennard Ng, Ser-Nam Lim, Gim Hee Lee
Content-based Video Retrieval (CBVR) is used on media-sharing platforms for applications such as video recommendation and filtering. To manage databases that scale to billions of v…
Visual Prompt Tuning
Menglin Jia, Luming Tang, Bor-Chun Chen +4
The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie, full fine-tuning. This paper introduces Visual Prompt Tuning (VPT) as a…