251 citations · 1k across the 82 of their papers we have counts for
83 papers
VideoStudio: Generating Consistent-Content and Multi-Scene Videos
Fuchen Long, Zhaofan Qiu, Ting Yao +1
The recent innovations and breakthroughs in diffusion models have significantly expanded the possibilities of generating high-quality videos for the given prompts. Most existing wo…
Bidirectional Knowledge Reconfiguration for Lightweight Point Cloud Analysis
Peipei Li, Xing Cui, Yibo Hu +3
Point cloud analysis faces computational system overhead, limiting its application on mobile or edge devices. Directly employing small models may result in a significant drop in pe…
Selective Volume Mixup for Video Action Recognition
Yi Tan, Zhaofan Qiu, Yanbin Hao +2
The recent advances in Convolutional Neural Networks (CNNs) and Vision Transformers have convincingly demonstrated high learning capability for video action recognition on large da…
Learning and Evaluating Human Preferences for Conversational Head Generation
Mohan Zhou, Yalong Bai, Wei Zhang +3
A reliable and comprehensive evaluation metric that aligns with manual preference assessments is crucial for conversational head video synthesis methods development. Existing quant…
Deep Equilibrium Multimodal Fusion
Jinhong Ni, Yalong Bai, Wei Zhang +2
Multimodal fusion integrates the complementary information present in multiple modalities and has gained much attention recently. Most existing fusion approaches either learn a fix…
Visual-Aware Text-to-Speech
Mohan Zhou, Yalong Bai, Wei Zhang +3
Dynamically synthesizing talking speech that actively responds to a listening head is critical during the face-to-face interaction. For example, the speaker could take advantage of…
Transforming Radiance Field with Lipschitz Network for Photorealistic 3D Scene Stylization
Zicheng Zhang, Yinglu Liu, Congying Han +3
Recent advances in 3D scene representation and novel view synthesis have witnessed the rise of Neural Radiance Fields (NeRFs). Nevertheless, it is not trivial to exploit NeRF for t…
Modality-Agnostic Debiasing for Single Domain Generalization
Sanqing Qu, Yingwei Pan, Guang Chen +3
Deep neural networks (DNNs) usually fail to generalize well to outside of distribution (OOD) data, especially in the extreme case of single domain generalization (single-DG) that t…
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…