441 citations · 1.5k across the 47 of their papers we have counts for
47 papers
Speed Co-Augmentation for Unsupervised Audio-Visual Pre-training
Jiangliu Wang, Jianbo Jiao, Yibing Song +5
This work aims to improve unsupervised audio-visual pre-training. Inspired by the efficacy of data augmentation in visual contrastive learning, we propose a novel speed co-augmenta…
Domain Generalization via Rationale Invariance
Liang Chen, Yong Zhang, Yibing Song +2
This paper offers a new perspective to ease the challenge of domain generalization, which involves maintaining robust results even in unseen environments. Our design focuses on the…
Advancing Visual Grounding with Scene Knowledge: Benchmark and Method
Zhihong Chen, Ruifei Zhang, Yibing Song +2
Visual grounding (VG) aims to establish fine-grained alignment between vision and language. Ideally, it can be a testbed for vision-and-language models to evaluate their understand…
Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation
Zunnan Xu, Zhihong Chen, Yong Zhang +3
Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few st…
Evolving Semantic Prototype Improves Generative Zero-Shot Learning
Shiming Chen, Wenjin Hou, Ziming Hong +5
In zero-shot learning (ZSL), generative methods synthesize class-related sample features based on predefined semantic prototypes. They advance the ZSL performance by synthesizing u…
Improved Test-Time Adaptation for Domain Generalization
Liang Chen, Yong Zhang, Yibing Song +2
The main challenge in domain generalization (DG) is to handle the distribution shift problem that lies between the training and test data. Recent studies suggest that test-time tra…
Efficient Video Action Detection with Token Dropout and Context Refinement
Lei Chen, Zhan Tong, Yibing Song +2
Streaming video clips with large-scale video tokens impede vision transformers (ViTs) for efficient recognition, especially in video action detection where sufficient spatiotempora…
Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning
Chongjian Ge, Jiangliu Wang, Zhan Tong +3
Contrastive learning methods train visual encoders by comparing views from one instance to others. Typically, the views created from one instance are set as positive, while views f…
CycleACR: Cycle Modeling of Actor-Context Relations for Video Action Detection
Lei Chen, Zhan Tong, Yibing Song +2
The relation modeling between actors and scene context advances video action detection where the correlation of multiple actors makes their action recognition challenging. Existing…
Human MotionFormer: Transferring Human Motions with Vision Transformers
Hongyu Liu, Xintong Han, Chengbin Jin +8
Human motion transfer aims to transfer motions from a target dynamic person to a source static one for motion synthesis. An accurate matching between the source person and the targ…
Image Inpainting via Iteratively Decoupled Probabilistic Modeling
Wenbo Li, Xin Yu, Kun Zhou +3
Generative adversarial networks (GANs) have made great success in image inpainting yet still have difficulties tackling large missing regions. In contrast, iterative probabilistic…
Delving StyleGAN Inversion for Image Editing: A Foundation Latent Space Viewpoint
Hongyu Liu, Yibing Song, Qifeng Chen
GAN inversion and editing via StyleGAN maps an input image into the embedding spaces (, , and ) to simultaneously maintain image fidelity a…
DiffusionDet: Diffusion Model for Object Detection
Shoufa Chen, Peize Sun, Yibing Song +1
We propose DiffusionDet, a new framework that formulates object detection as a denoising diffusion process from noisy boxes to object boxes. During the training stage, object boxes…
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations
Yiming Zhu, Hongyu Liu, Yibing Song +5
Free-form text prompts allow users to describe their intentions during image manipulation conveniently. Based on the visual latent space of StyleGAN[21] and text embedding space of…
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Shoufa Chen, Chongjian Ge, Zhan Tong +4
Pretraining Vision Transformers (ViTs) has achieved great success in visual recognition. A following scenario is to adapt a ViT to various image and video recognition tasks. The ad…
Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection
Liang Chen, Yong Zhang, Yibing Song +2
Recent studies in deepfake detection have yielded promising results when the training and testing face forgeries are from the same dataset. However, the problem remains challenging…
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Zhan Tong, Yibing Song, Jue Wang +1
Pre-training video transformers on extra large-scale datasets is generally required to achieve premier performance on relatively small datasets. In this paper, we show that video m…
Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations
Youwei Liang, Chongjian Ge, Zhan Tong +3
Vision Transformers (ViTs) take all the image patches as tokens and construct multi-head self-attention (MHSA) among them. Complete leverage of these image tokens brings redundant…
MetaDance: Few-shot Dancing Video Retargeting via Temporal-aware Meta-learning
Yuying Ge, Yibing Song, Ruimao Zhang +1
Dancing video retargeting aims to synthesize a video that transfers the dance movements from a source video to a target person. Previous work need collect a several-minute-long vid…
DynaMixer: A Vision MLP Architecture with Dynamic Mixing
Ziyu Wang, Wenhao Jiang, Yiming Zhu +3
Recently, MLP-like vision models have achieved promising performances on mainstream visual recognition tasks. In contrast with vision transformers and CNNs, the success of MLP-like…
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
Chongjian Ge, Youwei Liang, Yibing Song +3
Studies on self-supervised visual representation learning (SSL) improve encoder backbones to discriminate training samples without labels. While CNN encoders via SSL achieve compar…
PD-GAN: Probabilistic Diverse GAN for Image Inpainting
Hongyu Liu, Ziyu Wan, Wei Huang +3
We propose PD-GAN, a probabilistic diverse GAN for image inpainting. Given an input image with arbitrary hole regions, PD-GAN produces multiple inpainting results with diverse and…
ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows
Jie An, Siyu Huang, Yibing Song +3
Universal style transfer retains styles from reference images in content images. While existing methods have achieved state-of-the-art style transfer performance, they are not awar…
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
Shuai Jia, Yibing Song, Chao Ma +1
Adversarial attack arises due to the vulnerability of deep neural networks to perceive input samples injected with imperceptible perturbations. Recently, adversarial attack has bee…