1.5k citations · 2k across the 15 of their papers we have counts for
17 papers
Temporal Perceiving Video-Language Pre-training
Fan Ma, Xiaojie Jin, Heng Wang +4
Video-Language Pre-training models have recently significantly improved various multi-modal downstream tasks. Previous dominant works mainly adopt contrastive learning to achieve g…
Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity
Weiyao Wang, Matt Feiszli, Heng Wang +2
Open-world instance segmentation is the task of grouping pixels into object instances without any pre-determined taxonomy. This is challenging, as state-of-the-art methods rely on…
PyTorchVideo: A Deep Learning Library for Video Understanding
Haoqi Fan, Tullie Murrell, Heng Wang +13
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tas…
Searching for Two-Stream Models in Multivariate Space for Video Recognition
Xinyu Gong, Heng Wang, Zheng Shou +3
Conventional video models rely on a single stream to capture the complex spatial-temporal features. Recent work on two-stream video models, such as SlowFast network and AssembleNet…
Unidentified Video Objects: A Benchmark for Dense, Open-World Segmentation
Weiyao Wang, Matt Feiszli, Heng Wang +1
Current state-of-the-art object detection and segmentation methods work well under the closed-world assumption. This closed-world setting assumes that the list of object categories…
Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories
Xitong Yang, Haoqi Fan, Lorenzo Torresani +2
The standard way of training video models entails sampling at each iteration a single clip from a video and optimizing the clip prediction with respect to the video-level label. We…