148 citations · 280 across the 11 of their papers we have counts for
11 papers
Audio-Enhanced Vision-Language Modeling with Latent Space Broadening for High Quality Data Expansion
Yu Sun, Yin Li, Ruixiao Sun +7
Transformer-based multimodal models are widely used in industrial-scale recommendation, search, and advertising systems for content understanding and relevance ranking. Enhancing l…
LaT: Latent Translation with Cycle-Consistency for Video-Text Retrieval
Jinbin Bai, Chunhui Liu, Feiyue Ni +4
Video-text retrieval is a class of cross-modal representation learning problems, where the goal is to select the video which corresponds to the text query between a given text quer…
SSCAP: Self-supervised Co-occurrence Action Parsing for Unsupervised Temporal Action Segmentation
Zhe Wang, Hao Chen, Xinyu Li +4
Temporal action segmentation is a task to classify each frame in the video with an action label. However, it is quite expensive to annotate every frame in a large corpus of videos…
VidTr: Video Transformer Without Convolutions
Yanyi Zhang, Xinyu Li, Chunhui Liu +6
We introduce Video Transformer (VidTr) with separable-attention for video classification. Comparing with commonly used 3D networks, VidTr is able to aggregate spatio-temporal infor…
TubeR: Tubelet Transformer for Video Action Detection
Jiaojiao Zhao, Yanyi Zhang, Xinyu Li +10
We propose TubeR: a simple solution for spatio-temporal video action detection. Different from existing methods that depend on either an off-line actor detector or hand-designed ac…
Selective Feature Compression for Efficient Activity Recognition Inference
Chunhui Liu, Xinyu Li, Hao Chen +2
Most action recognition solutions rely on dense sampling to precisely cover the informative temporal clip. Extensively searching temporal region is expensive for a real-world appli…
NUTA: Non-uniform Temporal Aggregation for Action Recognition
Xinyu Li, Chunhui Liu, Bing Shuai +3
In the world of action recognition research, one primary focus has been on how to construct and train networks to model the spatial-temporal volume of an input video. These methods…
A Comprehensive Study of Deep Video Action Recognition
Yi Zhu, Xinyu Li, Chunhui Liu +7
Video action recognition is one of the representative tasks for video understanding. Over the last decade, we have witnessed great advancements in video action recognition thanks t…
Triplet Online Instance Matching Loss for Person Re-identification
Ye Li, Guangqiang Yin, Chunhui Liu +2
Mining the shared features of same identity in different scene, and the unique features of different identity in same scene, are most significant challenges in the field of person…
Patch Correspondences for Interpreting Pixel-level CNNs
Victor Fragoso, Chunhui Liu, Aayush Bansal +1
We present compositional nearest neighbors (CompNN), a simple approach to visually interpreting distributed representations learned by a convolutional neural network (CNN) for pixe…
PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding
Chunhui Liu, Yueyu Hu, Yanghao Li +2
Despite the fact that many 3D human activity benchmarks being proposed, most existing action datasets focus on the action recognition tasks for the segmented videos. There is a lac…