166 citations · 644 across the 58 of their papers we have counts for
12 papers · 1 filter
DBA: Efficient Transformer with Dynamic Bilinear Low-Rank Attention
Bosheng Qin, Juncheng Li, Siliang Tang +1
Many studies have been conducted to improve the efficiency of Transformer from quadric to linear. Among them, the low-rank-based methods aim to learn the projection matrices to com…
Fine-Grained Semantically Aligned Vision-Language Pre-Training
Juncheng Li, Xin He, Longhui Wei +6
Large-scale vision-language pre-training has shown impressive advances in a wide range of downstream tasks. Existing methods mainly model the cross-modal alignment by the similarit…
Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos
Juncheng Li, Junlin Xie, Linchao Zhu +8
Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion c…
BOSS: Bottom-up Cross-modal Semantic Composition with Hybrid Counterfactual Training for Robust Content-based Image Retrieval
Wenqiao Zhang, Jiannan Guo, Mengze Li +5
Content-Based Image Retrieval (CIR) aims to search for a target image by concurrently comprehending the composition of an example image and a complementary text, which potentially…
ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022
Naiyuan Liu, Xiaohan Wang, Xiaobo Li +2
In this report, we present the ReLER@ZJU-Alibaba submission to the Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2022. Given a video clip and a text query, the goal of thi…
Slimmable Domain Adaptation
Rang Meng, Weijie Chen, Shicai Yang +7
Vanilla unsupervised domain adaptation methods tend to optimize the model with fixed neural architecture, which is not very practical in real-world scenarios since the target data…
Label Matching Semi-Supervised Object Detection
Binbin Chen, Weijie Chen, Shicai Yang +6
Semi-supervised object detection has made significant progress with the development of mean teacher driven self-training. Despite the promising results, the label mismatch problem…
Learning Domain Adaptive Object Detection with Probabilistic Teacher
Meilin Chen, Weijie Chen, Shicai Yang +8
Self-training for unsupervised domain adaptive object detection is a challenging task, of which the performance depends heavily on the quality of pseudo boxes. Despite the promisin…
Transductive CLIP with Class-Conditional Contrastive Learning
Junchu Huang, Weijie Chen, Shicai Yang +3
Inspired by the remarkable zero-shot generalization capacity of vision-language pre-trained model, we seek to leverage the supervision from CLIP model to alleviate the burden of da…
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-Reptile
Dong Chen, Lingfei Wu, Siliang Tang +3
Recent years have seen a surge of interest in meta-learning techniques for tackling the few-shot learning (FSL) problem. However, the meta-learner is prone to overfitting since the…
Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence Learning
Juncheng Li, Junlin Xie, Long Qian +6
Temporal grounding in videos aims to localize one target video segment that semantically corresponds to a given query sentence. Thanks to the semantic diversity of natural language…
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images
Xiaoqiang Wang, Lei Zhu, Siliang Tang +5
Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the de…