4 citations · 13 across the 20 of their papers we have counts for
17 papers · 1 filter
VIABench: A Comprehensive Video Benchmark Collected from Blind Individuals for Visual Impairment Assistance
Yunfeng Liu, Yuandong Yang, Jiarui Han +5
Visually impaired individuals (VIIs) encounter significant daily challenges due to limited access to visual information. Although Multimodal Large Language Models (MLLMs) have achi…
VL-UniTrack: A Unified Framework with Visual-Language Prompts for UAV-Ground Visual Tracking
Boyue Xu, Ruichao Hou, Tongwei Ren +1
UAV-ground visual tracking (UGVT) aims to simultaneously track the same object from both the UAV and the ground view. However, existing two-stream methods suffer from isolated feat…
VMonarch: Efficient Video Diffusion Transformers with Structured Attention
Cheng Liang, Haoxian Chen, Liang Hou +4
The quadratic complexity of the attention mechanism severely limits the context scalability of Video Diffusion Transformers (DiTs). We find that the highly sparse spatio-temporal a…
SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation
Jiaming Zhang, Shengming Cao, Rui Li +8
Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Binding process of the dominant Refer…
SAM 2++: Tracking Anything at Any Granularity
Jiaming Zhang, Cheng Liang, Yichun Yang +7
Due to the varying granularity of target states across different tasks, most existing trackers are tailored to a single task, which specificity limits their generalization, prevent…
MotionRAG: Motion Retrieval-Augmented Image-to-Video Generation
Chenhui Zhu, Yilu Wu, Shuai Wang +2
Image-to-video generation has made remarkable progress with the advancements in diffusion models, yet generating videos with realistic motion remains highly challenging. This diffi…
CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning
Jiange Yang, Yansong Shi, Haoyi Zhu +6
Unsupervised learning of latent motion from Internet videos is crucial for robot learning. Existing discrete methods generally mitigate the shortcut learning caused by extracting e…
RGB-D Tracking via Hierarchical Modality Aggregation and Distribution Network
Boyue Xu, Yi Xu, Ruichao Hou +3
The integration of dual-modal features has been pivotal in advancing RGB-Depth (RGB-D) tracking. However, current trackers are less efficient and focus solely on single-level featu…
RGB-D Video Object Segmentation via Enhanced Multi-store Feature Memory
Boyue Xu, Ruichao Hou, Tongwei Ren +1
The RGB-Depth (RGB-D) Video Object Segmentation (VOS) aims to integrate the fine-grained texture information of RGB with the spatial geometric clues of depth modality, boosting the…
Efficient Test-Time Prompt Tuning for Vision-Language Models
Yuhan Zhu, Guozhen Zhang, Chen Xu +4
Vision-language models have showcased impressive zero-shot classification capabilities when equipped with suitable text prompts. Previous studies have shown the effectiveness of te…
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation
Yuhan Zhu, Yuyang Ji, Zhiyu Zhao +2
Pre-trained vision-language models (VLMs) have shown impressive results in various visual classification tasks. However, we often fail to fully unleash their potential when adaptin…
Open-Vocabulary Spatio-Temporal Action Detection
Tao Wu, Shuqiu Ge, Jie Qin +2
Spatio-temporal action detection (STAD) is an important fine-grained video understanding task. Current methods require box and label supervision for all action classes in advance.…
STMixer: A One-Stage Sparse Action Detector
Tao Wu, Mengqi Cao, Ziteng Gao +2
Traditional video action detectors typically adopt the two-stage pipeline, where a person detector is first employed to generate actor boxes and then 3D RoIAlign is used to extract…
SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos
Tao Wu, Runyu He, Gangshan Wu +1
Video-based visual relation detection tasks, such as video scene graph generation, play important roles in fine-grained video understanding. However, current video visual relation…
Dual DETRs for Multi-Label Temporal Action Detection
Yuhan Zhu, Guozhen Zhang, Jing Tan +2
Temporal Action Detection (TAD) aims to identify the action boundaries and the corresponding category within untrimmed videos. Inspired by the success of DETR in object detection,…
Asymmetric Masked Distillation for Pre-Training Small Foundation Models
Zhiyu Zhao, Bingkun Huang, Sen Xing +3
Self-supervised foundation models have shown great potential in computer vision thanks to the pre-training paradigm of masked autoencoding. Scale is a primary factor influencing th…
Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation
Jiaming Zhang, Yutao Cui, Gangshan Wu +1
Current prevailing Video Object Segmentation methods follow the pipeline of extraction-then-matching, which first extracts features on current and reference frames independently, a…