43 citations · 230 across the 21 of their papers we have counts for
21 papers
When Parameter-efficient Tuning Meets General-purpose Vision-language Models
Yihang Zhai, Haixin Wang, Jianlong Chang +4
Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate mul…
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models
Lingxi Xie, Longhui Wei, Xiaopeng Zhang +4
The AI community has been pursuing algorithms known as artificial general intelligence (AGI) that apply to any kind of real-world problem. Recently, chat systems powered by large l…
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang +5
Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…
Visual Tuning
Bruce X. B. Yu, Jianlong Chang, Haixin Wang +9
Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visu…
LION: Implicit Vision Prompt Tuning
Haixin Wang, Jianlong Chang, Xiao Luo +3
Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has pr…
Constraint and Union for Partially-Supervised Temporal Sentence Grounding
Chen Ju, Haicheng Wang, Jinxiang Liu +5
Temporal sentence grounding aims to detect the event timestamps described by the natural language query from given untrimmed videos. The existing fully-supervised setting achieves…
Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization
Chen Ju, Kunhao Zheng, Jinxiang Liu +5
Weakly-supervised temporal action localization (WTAL) learns to detect and classify action instances with only category labels. Most methods widely adopt the off-the-shelf Classifi…
Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training
Junfan Lin, Jianlong Chang, Lingbo Liu +4
Text-to-motion generation is an emerging and challenging problem, which aims to synthesize motion with the same semantics as the input text. However, due to the lack of diverse lab…
Towards a Unified View on Visual Parameter-Efficient Transfer Learning
Bruce X. B. Yu, Jianlong Chang, Lingbo Liu +2
Parameter efficient transfer learning (PETL) aims at making good use of the representation knowledge in the pre-trained large models by fine-tuning a small number of parameters. Re…
Pro-tuning: Unified Prompt Tuning for Vision Tasks
Xing Nie, Bolin Ni, Jianlong Chang +6
In computer vision, fine-tuning is the de-facto approach to leverage pre-trained vision models to perform downstream tasks. However, deploying it in practice is quite challenging,…
Prompt-Matched Semantic Segmentation
Lingbo Liu, Jianlong Chang, Bruce X. B. Yu +3
The objective of this work is to explore how to effectively and efficiently adapt pre-trained visual foundation models to various downstream tasks of semantic segmentation. Previou…
Fine-grained Retrieval Prompt Tuning
Shijie Wang, Jianlong Chang, Zhihui Wang +3
Fine-grained object retrieval aims to learn discriminative representation to retrieve visually similar objects. However, existing top-performing works usually impose pairwise simil…
HiVLP: Hierarchical Vision-Language Pre-Training for Fast Image-Text Retrieval
Feilong Chen, Xiuyi Chen, Jiaxin Shi +3
In the past few years, the emergence of vision-language pre-training (VLP) has brought cross-modal retrieval to a new era. However, due to the latency and computation demand, it is…
Differentiable Convolution Search for Point Cloud Processing
Xing Nie, Yongcheng Liu, Shaohong Chen +6
Exploiting convolutional neural networks for point cloud processing is quite challenging, due to the inherent irregular distribution and discrete shape representation of point clou…
What Is Considered Complete for Visual Recognition?
Lingxi Xie, Xiaopeng Zhang, Longhui Wei +2
This is an opinion paper. We hope to deliver a key message that current visual recognition systems are far from complete, i.e., recognizing everything that human can recognize, yet…
Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration
Xingyu Chen, Yufeng Liu, Chongyang Ma +6
Recent years have witnessed significant progress in 3D hand mesh recovery. Nevertheless, because of the intrinsic 2D-to-3D ambiguity, recovering camera-space 3D information from a…
Can Semantic Labels Assist Self-Supervised Visual Representation Learning?
Longhui Wei, Lingxi Xie, Jianzhong He +5
Recently, contrastive learning has largely advanced the progress of unsupervised visual representation learning. Pre-trained on ImageNet, some self-supervised algorithms reported h…
Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
Lingxi Xie, Xin Chen, Kaifeng Bi +8
Neural architecture search (NAS) has attracted increasing attentions in both academia and industry. In the early age, researchers mostly applied individual search methods which sam…
Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification
Guan-An Wang, Tianzhu Zhang. Yang Yang, Jian Cheng +3
RGB-Infrared (IR) person re-identification is very challenging due to the large cross-modality variations between RGB and IR images. The key solution is to learn aligned features t…
Differentiable Architecture Search with Ensemble Gumbel-Softmax
Jianlong Chang, Xinbang Zhang, Yiwen Guo +3
For network architecture search (NAS), it is crucial but challenging to simultaneously guarantee both effectiveness and efficiency. Towards achieving this goal, we develop a differ…
Deep Discriminative Clustering Analysis
Jianlong Chang, Yiwen Guo, Lingfeng Wang +3
Traditional clustering methods often perform clustering with low-level indiscriminative representations and ignore relationships between patterns, resulting in slight achievements…