85 citations · 199 across the 22 of their papers we have counts for
22 papers
MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons
Kehong Gong, Zhengyu Wen, Dao Thien Phong +10
Recent methods for arbitrary-skeleton motion capture from monocular video follow a factorized pipeline, where a Video-to-Pose network predicts joint positions and an analytical inv…
SWiT-4D: Sliding-Window Transformer for Lossless and Parameter-Free Temporal 4D Generation
Kehong Gong, Zhengyu Wen, Mingxi Xu +9
Despite significant progress in 4D content generation, the conversion of monocular videos into high-quality animated 3D assets with explicit 4D meshes remains considerably challeng…
MoCapAnything: Unified 3D Motion Capture for Arbitrary Skeletons from Monocular Videos
Kehong Gong, Zhengyu Wen, Weixia He +8
Motion capture now underpins content creation far beyond digital humans, yet most existing pipelines remain species- or template-specific. We formalize this gap as Category-Agnosti…
Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach
Taolin Zhang, Jiawang Bai, Zhihe Lu +4
Recent works on parameter-efficient transfer learning (PETL) show the potential to adapt a pre-trained Vision Transformer to downstream recognition tasks with only a few learnable…
FCA-RAC: First Cycle Annotated Repetitive Action Counting
Jiada Lu, WeiWei Zhou, Xiang Qian +5
Repetitive action counting quantifies the frequency of specific actions performed by individuals. However, existing action-counting datasets have limited action diversity, potentia…
DreamDrone: Text-to-Image Diffusion Models are Zero-shot Perpetual View Generators
Hanyang Kong, Dongze Lian, Michael Bi Mi +1
We introduce DreamDrone, a novel zero-shot and training-free pipeline for generating unbounded flythrough scenes from textual prompts. Different from other methods that focus on wa…
TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding
Shuo Wang, Jing Li, Zibo Zhao +5
Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc. The key aspect of this problem is to learn…
GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph
Xin Li, Dongze Lian, Zhihe Lu +3
Adapter-style efficient transfer learning (ETL) has shown excellent performance in the tuning of vision-language models (VLMs) under the low-data regime, where only a few additiona…
Priority-Centric Human Motion Generation in Discrete Latent Space
Hanyang Kong, Kehong Gong, Dongze Lian +2
Text-to-motion generation is a formidable task, aiming to produce human motions that align with the input text while also adhering to human capabilities and physical laws. While th…
Dataset Quantization
Daquan Zhou, Kai Wang, Jianyang Gu +5
State-of-the-art deep neural networks are trained with large amounts (millions or even billions) of data. The expensive computation and memory costs make it difficult to train them…
Revisiting Event-based Video Frame Interpolation
Jiaben Chen, Yichen Zhu, Dongze Lian +7
Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining bot…
TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integration
Kehong Gong, Dongze Lian, Heng Chang +5
We propose a novel task for generating 3D dance movements that simultaneously incorporate both text and music modalities. Unlike existing works that generate dance movements using…
Weakly Supervised Video Representation Learning with Unaligned Text for Sequential Videos
Sixun Dong, Huazhang Hu, Dongze Lian +3
Sequential video understanding, as an emerging video understanding task, has driven lots of researchers' attention because of its goal-oriented nature. This paper studies weakly su…
iQuery: Instruments as Queries for Audio-Visual Sound Separation
Jiaben Chen, Renrui Zhang, Dongze Lian +3
Current audio-visual separation methods share a standard architecture design where an audio encoder-decoder network is fused with visual encoding features at the encoder bottleneck…
Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning
Dongze Lian, Daquan Zhou, Jiashi Feng +1
Existing fine-tuning methods either tune all parameters of the pre-trained model (full fine-tuning), which is not efficient, or only tune the last linear layer (linear probing), wh…
TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting
Huazhang Hu, Sixun Dong, Yiqun Zhao +3
Counting repetitive actions are widely seen in human activities such as physical exercise. Existing methods focus on performing repetitive action counting in short videos, which is…
SVIP: Sequence VerIfication for Procedures in Videos
Yicheng Qian, Weixin Luo, Dongze Lian +3
In this paper, we propose a novel sequence verification task that aims to distinguish positive video pairs performing the same action sequence from negative ones with step-level tr…
AS-MLP: An Axial Shifted MLP Architecture for Vision
Dongze Lian, Zehao Yu, Xing Sun +1
An Axial Shifted MLP architecture (AS-MLP) is proposed in this paper. Different from MLP-Mixer, where the global spatial feature is encoded for information flow through matrix tran…
Look Before You Leap: Learning Landmark Features for One-Stage Visual Grounding
Binbin Huang, Dongze Lian, Weixin Luo +1
An LBYL (`Look Before You Leap') Network is proposed for end-to-end trainable one-stage visual grounding. The idea behind LBYL-Net is intuitive and straightforward: we follow a lan…
Believe It or Not, We Know What You Are Looking at!
Dongze Lian, Zehao Yu, Shenghua Gao
By borrowing the wisdom of human in gaze following, we propose a two-stage solution for gaze point prediction of the target persons in a scene. Specifically, in the first stage, bo…
Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding
Zehao Yu, Jia Zheng, Dongze Lian +2
Single-image piece-wise planar 3D reconstruction aims to simultaneously segment plane instances and recover 3D plane parameters from an image. Most recent approaches leverage convo…
Future Frame Prediction for Anomaly Detection -- A New Baseline
Wen Liu, Weixin Luo, Dongze Lian +1
Anomaly detection in videos refers to the identification of events that do not conform to expected behavior. However, almost all existing methods tackle the problem by minimizing t…