17 citations · 37 across the 22 of their papers we have counts for
25 papers · 1 filter
UniLayDiff: A Unified Diffusion Transformer for Content-Aware Layout Generation
Zeyang Liu, Le Wang, Sanping Zhou +4
Content-aware layout generation is a critical task in graphic design automation, focused on creating visually appealing arrangements of elements that seamlessly blend with a given…
SAMPO:Scale-wise Autoregression with Motion PrOmpt for generative world models
Sen Wang, Jingyi Tian, Le Wang +7
World models allow agents to simulate the consequences of actions in imagined environments for planning, control, and long-horizon decision-making. However, existing autoregressive…
Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection
Canhui Tang, Sanping Zhou, Haoyue Shi +1
Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due to various practical concerns,…
Embracing Aleatoric Uncertainty: Generating Diverse 3D Human Motion
Zheng Qin, Yabing Wang, Minghui Yang +3
Generating 3D human motions from text is a challenging yet valuable task. The key aspects of this task are ensuring text-motion consistency and achieving generation diversity. Alth…
Enhancing Mamba Decoder with Bidirectional Interaction in Multi-Task Dense Prediction
Mang Cao, Sanping Zhou, Yizhe Li +3
Sufficient cross-task interaction is crucial for success in multi-task dense prediction. However, sufficient interaction often results in high computational complexity, forcing exi…
TSPO: Temporal Sampling Policy Optimization for Long-form Video Language Understanding
Canhui Tang, Zifan Han, Hongbo Sun +7
Multimodal Large Language Models (MLLMs) have demonstrated significant progress in vision-language tasks, yet they still face challenges when processing long-duration video inputs.…
PR-DETR: Injecting Position and Relation Prior for Dense Video Captioning
Yizhe Li, Sanping Zhou, Zheng Qin +1
Dense video captioning is a challenging task that aims to localize and caption multiple events in an untrimmed video. Recent studies mainly follow the transformer-based architectur…
LayoutRAG: Retrieval-Augmented Model for Content-agnostic Conditional Layout Generation
Yuxuan Wu, Le Wang, Sanping Zhou +3
Controllable layout generation aims to create plausible visual arrangements of element bounding boxes within a graphic design according to certain optional constraints, such as the…
From Mapping to Composing: A Two-Stage Framework for Zero-shot Composed Image Retrieval
Yabing Wang, Zhuotao Tian, Qingpei Guo +4
Composed Image Retrieval (CIR) is a challenging multimodal task that retrieves a target image based on a reference image and accompanying modification text. Due to the high cost of…
Moment Quantization for Video Temporal Grounding
Xiaolong Sun, Le Wang, Sanping Zhou +5
Video temporal grounding is a critical video understanding task, which aims to localize moments relevant to a language description. The challenge of this task lies in distinguishin…
RSRNav: Reasoning Spatial Relationship for Image-Goal Navigation
Zheng Qin, Le Wang, Yabing Wang +3
Recent image-goal navigation (ImageNav) methods learn a perception-action policy by separately capturing semantic features of the goal and egocentric images, then passing them to a…
Versatile Multimodal Controls for Expressive Talking Human Animation
Zheng Qin, Ruobing Zheng, Yabing Wang +5
In filmmaking, directors typically allow actors to perform freely based on the script before providing specific guidance on how to present key actions. AI-generated content faces s…
Referencing Where to Focus: Improving VisualGrounding with Referential Query
Yabing Wang, Zhuotao Tian, Qingpei Guo +4
Visual Grounding aims to localize the referring object in an image given a natural language expression. Recent advancements in DETR-based visual grounding methods have attracted co…
Towards Generalizable Multi-Object Tracking
Zheng Qin, Le Wang, Sanping Zhou +3
Multi-Object Tracking MOT encompasses various tracking scenarios, each characterized by unique traits. Effective trackers should demonstrate a high degree of generalizability acros…
Diversifying Query: Region-Guided Transformer for Temporal Sentence Grounding
Xiaolong Sun, Liushuai Shi, Le Wang +4
Temporal sentence grounding is a challenging task that aims to localize the moment spans relevant to a language description. Although recent DETR-based models have achieved notable…
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection
Canhui Tang, Sanping Zhou, Yizhe Li +2
With the wide application of knowledge distillation between an ImageNet pre-trained teacher model and a learnable student model, unsupervised anomaly detection has witnessed a sign…
Learning Discriminative Spatio-temporal Representations for Semi-supervised Action Recognition
Yu Wang, Sanping Zhou, Kun Xia +1
Semi-supervised action recognition aims to improve spatio-temporal reasoning ability with a few labeled data in conjunction with a large amount of unlabeled data. Albeit recent adv…
Boosting Semi-Supervised Temporal Action Localization by Learning from Non-Target Classes
Kun Xia, Le Wang, Sanping Zhou +2
The crux of semi-supervised temporal action localization (SS-TAL) lies in excavating valuable information from abundant unlabeled videos. However, current approaches predominantly…
Recurrent Aligned Network for Generalized Pedestrian Trajectory Prediction
Yonghao Dong, Le Wang, Sanping Zhou +2
Pedestrian trajectory prediction is a crucial component in computer vision and robotics, but remains challenging due to the domain shift problem. Previous studies have tried to tac…
Sparse Pedestrian Character Learning for Trajectory Prediction
Yonghao Dong, Le Wang, Sanpin Zhou +2
Pedestrian trajectory prediction in a first-person view has recently attracted much attention due to its importance in autonomous driving. Recent work utilizes pedestrian character…
Single-Shot and Multi-Shot Feature Learning for Multi-Object Tracking
Yizhe Li, Sanping Zhou, Zheng Qin +3
Multi-Object Tracking (MOT) remains a vital component of intelligent video analysis, which aims to locate targets and maintain a consistent identity for each target throughout a vi…
MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking
Zheng Qin, Sanping Zhou, Le Wang +3
The main challenge of Multi-Object Tracking~(MOT) lies in maintaining a continuous trajectory for each target. Existing methods often learn reliable motion patterns to match the sa…
Learning to Refactor Action and Co-occurrence Features for Temporal Action Localization
Kun Xia, Le Wang, Sanping Zhou +2
The main challenge of Temporal Action Localization is to retrieve subtle human actions from various co-occurring ingredients, e.g., context and background, in an untrimmed video. W…
Social Interpretable Tree for Pedestrian Trajectory Prediction
Liushuai Shi, Le Wang, Chengjiang Long +4
Understanding the multiple socially-acceptable future behaviors is an essential task for many vision applications. In this paper, we propose a tree-based method, termed as Social I…