64 citations · 292 across the 46 of their papers we have counts for
21 papers · 1 filter
3D-TOGO: Towards Text-Guided Cross-Category 3D Object Generation
Zutao Jiang, Guansong Lu, Xiaodan Liang +4
Text-guided 3D object generation aims to generate 3D objects described by user-defined captions, which paves a flexible way to visualize what we imagined. Although some works have…
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning
Zaiyu Huang, Hanhui Li, Zhenyu Xie +3
In this paper, we target image-based person-to-person virtual try-on in the presence of diverse poses and large viewpoint variations. Existing methods are restricted in this settin…
Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection
Yanxin Long, Jianhua Han, Runhui Huang +4
Inspired by the success of vision-language methods (VLMs) in zero-shot classification, recent works attempt to extend this line of work into object detection by leveraging the loca…
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection
Lewei Yao, Jianhua Han, Youpeng Wen +6
Open-world object detection, as a more general and challenging goal, aims to recognize and localize objects described by arbitrary category names. The recent work GLIP formulates t…
Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning
Yi Cheng, Wenge Liu, Wenjie Li +5
Providing Emotional Support (ES) to soothe people in emotional distress is an essential capability in social interactions. Most existing researches on building ES conversation syst…
Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving
Xiwen Liang, Yangxin Wu, Jianhua Han +3
Aiming towards a holistic understanding of multiple downstream tasks simultaneously, there is a need for extracting features with better transferability. Though many latest self-su…
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design
Xujie Zhang, Yu Sha, Michael C. Kampffmeyer +5
Cross-modal fashion image synthesis has emerged as one of the most promising directions in the generation domain due to the vast untapped potential of incorporating multiple modali…
Composable Text Controls in Latent Space with ODEs
Guangyi Liu, Zeyu Feng, Yuan Gao +7
Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and…
PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on
Zhenyu Xie, Zaiyu Huang, Fuwei Zhao +5
Image-based virtual try-on is one of the most promising applications of human-centric image generation due to its tremendous real-world potential. In this work, we take a step forw…
SiRi: A Simple Selective Retraining Mechanism for Transformer-based Visual Grounding
Mengxue Qu, Yu Wu, Wu Liu +5
In this paper, we investigate how to achieve better visual grounding with modern vision-language transformers, and propose a simple yet powerful Selective Retraining (SiRi) mechani…
Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding
Quande Liu, Youpeng Wen, Jianhua Han +3
To bridge the gap between supervised semantic segmentation and real-world applications that acquires one model to recognize arbitrary new concepts, recent zero-shot segmentation at…
Entity-Graph Enhanced Cross-Modal Pretraining for Instance-level Product Retrieval
Xiao Dong, Xunlin Zhan, Yunchao Wei +5
Our goal in this research is to study a more realistic environment in which we can conduct weakly-supervised multi-modal instance-level product retrieval for fine-grained product c…
Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
Binbin Yang, Xinchi Deng, Han Shi +6
Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual class…
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
Jiahui Gao, Renjie Pi, Yong Lin +7
There is a rising interest in further exploring the zero-shot learning potential of large pre-trained language models (PLMs). A new paradigm called data-generation-based zero-shot…
Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture Search
Minbin Huang, Zhijian Huang, Changlin Li +4
Neural Architecture Search (NAS) aims to find efficient models for multiple tasks. Beyond seeking solutions for a single task, there are surging interests in transferring network d…
Dressing in the Wild by Watching Dance Videos
Xin Dong, Fuwei Zhao, Zhenyu Xie +6
While significant progress has been made in garment transfer, one of the most applicable directions of human-centric image generation, existing works overlook the in-the-wild image…
Laneformer: Object-aware Row-Column Transformers for Lane Detection
Jianhua Han, Xiajun Deng, Xinyue Cai +4
We present Laneformer, a conceptually simple yet powerful transformer-based architecture tailored for lane detection that is a long-standing research topic for visual perception in…
Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration
Xiwen Liang, Fengda Zhu, Lingling Li +2
Vision-language navigation (VLN) is a challenging task due to its large searching space in the environment. To address this problem, previous works have proposed some methods of fi…
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving
Kaican Li, Kai Chen, Haoyu Wang +10
Contemporary deep-learning object detection methods for autonomous driving usually assume prefixed categories of common traffic participants, such as pedestrians and cars. Most exi…
Revisiting Over-smoothing in BERT from the Perspective of Graph
Han Shi, Jiahui Gao, Hang Xu +5
Recently over-smoothing phenomenon of Transformer-based models is observed in both vision and language fields. However, no existing work has delved deeper to further investigate th…
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
Jiaxi Gu, Xiaojun Meng, Guansong Lu +9
Vision-Language Pre-training (VLP) models have shown remarkable performance on various downstream tasks. Their success heavily relies on the scale of pre-trained cross-modal datase…