663 citations · 2.2k across the 65 of their papers we have counts for
71 papers
IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection
Junbo Yin, Jianbing Shen, Runnan Chen +4
Bird's eye view (BEV) representation has emerged as a dominant solution for describing 3D space in autonomous driving scenarios. However, objects in the BEV representation typicall…
ClusterFormer: Clustering As A Universal Visual Learner
James C. Liang, Yiming Cui, Qifan Wang +3
This paper presents CLUSTERFORMER, a universal vision model that is based on the CLUSTERing paradigm with TransFORMER. It comprises two novel designs: 1. recurrent cross-attention…
LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoning
Liulei Li, Wenguan Wang, Yi Yang
Current high-performance semantic segmentation models are purely data-driven sub-symbolic approaches and blind to the structured nature of the visual world. This is in stark contra…
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation
Chen Liang, Wenguan Wang, Jiaxu Miao +1
Recent advances in semi-supervised semantic segmentation have been heavily reliant on pseudo labeling to compensate for limited labeled data, disregarding the valuable relational k…
Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation
Jinyu Chen, Wenguan Wang, Si Liu +2
Audio-visual navigation is an audio-targeted wayfinding task where a robot agent is entailed to travel a never-before-seen 3D environment towards the sounding source. In this artic…
DREAMWALKER: Mental Planning for Continuous Vision-Language Navigation
Hanqing Wang, Wei Liang, Luc Van Gool +1
VLN-CE is a recently released embodied task, where AI agents need to navigate a freely traversable environment to reach a distant target location, given language instructions. It p…
Bird's-Eye-View Scene Graph for Vision-Language Navigation
Rui Liu, Xiaohan Wang, Wenguan Wang +1
Vision-language navigation (VLN), which entails an agent to navigate 3D environments following human instructions, has shown great advances. However, current agents are built upon…
Clustering based Point Cloud Representation Learning for 3D Analysis
Tuo Feng, Wenguan Wang, Xiaohan Wang +2
Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the…
E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning
Cheng Han, Qifan Wang, Yiming Cui +4
As the size of transformer-based models continues to grow, fine-tuning these large-scale pretrained vision models for new tasks has become increasingly parameter-intensive. Paramet…
Kefa: A Knowledge Enhanced and Fine-grained Aligned Speaker for Navigation Instruction Generation
Haitian Zeng, Xiaohan Wang, Wenguan Wang +1
We introduce a novel speaker model \textsc{Kefa} for navigation instruction generation. The existing speaker models in Vision-and-Language Navigation suffer from the large domain g…
Large-Scale Person Detection and Localization using Overhead Fisheye Cameras
Lu Yang, Liulei Li, Xueshi Xin +3
Location determination finds wide applications in daily life. Instead of existing efforts devoted to localizing tourist photos captured by perspective cameras, in this article, we…
CLUSTSEG: Clustering for Universal Segmentation
James Liang, Tianfei Zhou, Dongfang Liu +1
We present CLUSTSEG, a general, transformer-based framework that tackles different image segmentation tasks (i.e., superpixel, semantic, instance, and panoptic) through a unified n…
Segment and Track Anything
Yangming Cheng, Liulei Li, Yuanyou Xu +4
This report presents a framework called Segment And Track Anything (SAMTrack) that allows users to precisely and effectively segment and track any object in a video. Additionally,…
Boosting Video Object Segmentation via Space-time Correspondence Learning
Yurong Zhang, Liulei Li, Wenguan Wang +3
Current top-leading solutions for video object segmentation (VOS) typically follow a matching-based regime: for each query frame, the segmentation mask is inferred according to its…
ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments
Dong An, Hanqing Wang, Wenguan Wang +4
Vision-language navigation is a task that requires an agent to follow instructions to navigate in environments. It becomes increasingly crucial in the field of embodied AI, with po…
Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation
Liulei Li, Wenguan Wang, Tianfei Zhou +2
The objective of this paper is self-supervised learning of video object segmentation. We develop a unified framework which simultaneously models cross-frame dense correspondence fo…
Lana: A Language-Capable Navigator for Instruction Following and Generation
Xiaohan Wang, Wenguan Wang, Jiayi Shao +1
Recently, visual-language navigation (VLN) -- entailing robot agents to follow navigation instructions -- has shown great advance. However, existing literature put most emphasis on…
Towards Versatile Embodied Navigation
Hanqing Wang, Wei Liang, Luc Van Gool +1
With the emergence of varied visual navigation tasks (e.g, image-/object-/audio-goal and vision-language navigation) that specify the target in different ways, the community has ma…
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
Chen Liang, Wenguan Wang, Jiaxu Miao +1
Prevalent semantic segmentation solutions are, in essence, a dense discriminative classifier of p(class|pixel feature). Though straightforward, this de facto paradigm neglects the…
Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computing
Wenguan Wang, Yi Yang, Fei Wu
Neural-symbolic computing (NeSy), which pursues the integration of the symbolic and statistical paradigms of cognition, has been an active research area of Artificial Intelligence…
Learning Equivariant Segmentation with Instance-Unique Querying
Wenguan Wang, James Liang, Dongfang Liu
Prevalent state-of-the-art instance segmentation methods fall into a query-based scheme, in which instance masks are derived by querying the image feature using a set of instance-a…
LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space
Xuekun Zhao, Pu Cao, Xiaoya Yang +3
As research on image inversion advances, the process is generally divided into two stages. The first step is Image Embedding, involves using an encoder or optimization procedure to…
Visual Recognition with Deep Nearest Centroids
Wenguan Wang, Cheng Han, Tianfei Zhou +1
We devise deep nearest centroids (DNC), a conceptually elegant yet surprisingly effective network for large-scale visual recognition, by revisiting Nearest Centroids, one of the mo…
Reference-based Image Super-Resolution with Deformable Attention Transformer
Jiezhang Cao, Jingyun Liang, Kai Zhang +4
Reference-based image super-resolution (RefSR) aims to exploit auxiliary reference (Ref) images to super-resolve low-resolution (LR) images. Recently, RefSR has been attracting gre…