251 citations · 1k across the 82 of their papers we have counts for
24 papers · 1 filter
Semantic-Conditional Diffusion Networks for Image Captioning
Jianjie Luo, Yehao Li, Yingwei Pan +4
Recent advances on text-to-image generation have witnessed the rise of diffusion models which act as powerful generative models. Nevertheless, it is not trivial to exploit such lat…
Dynamic Temporal Filtering in Video Models
Fuchen Long, Zhaofan Qiu, Yingwei Pan +3
Video temporal dynamics is conventionally modeled with 3D spatial-temporal kernel or its factorized version comprised of 2D spatial kernel and 1D temporal kernel. The modeling powe…
SPE-Net: Boosting Point Cloud Analysis via Rotation Robustness Enhancement
Zhaofan Qiu, Yehao Li, Yu Wang +3
In this paper, we propose a novel deep architecture tailored for 3D point cloud applications, named as SPE-Net. The embedded ``Selective Position Encoding (SPE)'' procedure relies…
Explaining Cross-Domain Recognition with Interpretable Deep Classifier
Yiheng Zhang, Ting Yao, Zhaofan Qiu +1
The recent advances in deep learning predominantly construct models in their internal representations, and it is opaque to explain the rationale behind and decisions to human users…
3D Cascade RCNN: High Quality Object Detection in Point Clouds
Qi Cai, Yingwei Pan, Ting Yao +1
Recent progress on 2D object detection has featured Cascade RCNN, which capitalizes on a sequence of cascade detectors to progressively improve proposal quality, towards high-quali…
Generalized One-shot Domain Adaptation of Generative Adversarial Networks
Zicheng Zhang, Yinglu Liu, Congying Han +3
The adaptation of a Generative Adversarial Network (GAN) aims to transfer a pre-trained GAN to a target domain with limited training data. In this paper, we focus on the one-shot c…
Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Jingyang Lin, Yu Wang, Qi Cai +4
Outlier detection tasks have been playing a critical role in AI safety. There has been a great challenge to deal with this task. Observations show that deep neural network classifi…
Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation
Hailin Shi, Hang Du, Yibo Hu +3
Human face images usually appear with wide range of visual scales. The existing face representations pursue the bandwidth of handling scale variation via multi-scale scheme that as…
Lightweight and Progressively-Scalable Networks for Semantic Segmentation
Yiheng Zhang, Ting Yao, Zhaofan Qiu +1
Multi-scale learning frameworks have been regarded as a capable class of models to boost semantic segmentation. The problem nevertheless is not trivial especially for the real-worl…
Dual Vision Transformer
Ting Yao, Yehao Li, Yingwei Pan +3
Prior works have proposed several strategies to reduce the computational cost of self-attention mechanism. Many of these works consider decomposing the self-attention procedure int…
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning
Ting Yao, Yingwei Pan, Yehao Li +2
Multi-scale Vision Transformer (ViT) has emerged as a powerful backbone for computer vision tasks, while the self-attention computation in Transformer scales quadratically w.r.t. t…
Bi-Calibration Networks for Weakly-Supervised Video Representation Learning
Fuchen Long, Ting Yao, Zhaofan Qiu +3
The leverage of large volumes of web videos paired with the searched queries or surrounding texts (e.g., title) offers an economic and extensible alternative to supervised video re…
Stand-Alone Inter-Frame Attention in Video Models
Fuchen Long, Zhaofan Qiu, Yingwei Pan +3
Motion, as the uniqueness of a video, has been critical to the development of video understanding models. Modern deep learning models leverage motion by either executing spatio-tem…
Comprehending and Ordering Semantics for Image Captioning
Yehao Li, Yingwei Pan, Ting Yao +1
Comprehending the rich semantics in an image and ordering them in linguistic order are essential to compose a visually-grounded and linguistically coherent description for image ca…
MLP-3D: A MLP-like 3D Architecture with Grouped Time Mixing
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo +1
Convolutional Neural Networks (CNNs) have been regarded as the go-to models for visual recognition. More recently, convolution-free networks, based on multi-head self-attention (MS…
Exploring Structure-aware Transformer over Interaction Proposals for Human-Object Interaction Detection
Yong Zhang, Yingwei Pan, Ting Yao +3
Recent high-performing Human-Object Interaction (HOI) detection techniques have been highly influenced by Transformer-based object detector (i.e., DETR). Nevertheless, most of them…
Silver-Bullet-3D at ManiSkill 2021: Learning-from-Demonstrations and Heuristic Rule-based Methods for Object Manipulation
Yingwei Pan, Yehao Li, Yiheng Zhang +5
This paper presents an overview and comparative analysis of our systems designed for the following two tracks in SAPIEN ManiSkill Challenge 2021: No Interaction Track: The No Inter…
Visualizing and Understanding Patch Interactions in Vision Transformer
Jie Ma, Yalong Bai, Bineng Zhong +3
Vision Transformer (ViT) has become a leading tool in various computer vision tasks, owing to its unique self-attention mechanism that learns visual representations explicitly thro…
Motion-Focused Contrastive Learning of Video Representations
Rui Li, Yiheng Zhang, Zhaofan Qiu +3
Motion, as the most distinct phenomenon in a video to involve the changes over time, has been unique and critical to the development of video representation learning. In this paper…
Representing Videos as Discriminative Sub-graphs for Action Recognition
Dong Li, Zhaofan Qiu, Yingwei Pan +3
Human actions are typically of combinatorial structures or patterns, i.e., subjects, objects, plus spatio-temporal interactions in between. Discovering such structures is therefore…
Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training
Yehao Li, Jiahao Fan, Yingwei Pan +3
Vision-language pre-training has been an emerging and fast-developing research topic, which transfers multi-modal knowledge from rich-resource pre-training task to limited-resource…
Smart Director: An Event-Driven Directing System for Live Broadcasting
Yingwei Pan, Yue Chen, Qian Bao +4
Live video broadcasting normally requires a multitude of skills and expertise with domain knowledge to enable multi-camera productions. As the number of cameras keep increasing, di…
Boosting Video Representation Learning with Multi-Faceted Integration
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo +3
Video content is multifaceted, consisting of objects, scenes, interactions or actions. The existing datasets mostly label only one of the facets for model training, resulting in th…
Condensing a Sequence to One Informative Frame for Video Recognition
Zhaofan Qiu, Ting Yao, Yan Shu +2
Video is complex due to large variations in motion and rich content in fine-grained visual details. Abstracting useful information from such information-intensive media requires ex…