224 citations · 2.3k across the 117 of their papers we have counts for
14 papers · 1 filter
Pixel2ISDF: Implicit Signed Distance Fields based Human Body Model from Multi-view and Multi-pose Images
Jianchuan Chen, Wentao Yi, Tiantian Wang +4
In this report, we focus on reconstructing clothed humans in the canonical space given multiple views and poses of a human as the input. To achieve this, we utilize the geometric p…
HS-Diffusion: Semantic-Mixing Diffusion for Head Swapping
Qinghe Wang, Lijie Liu, Miao Hua +5
Image-based head swapping task aims to stitch a source head to another source body flawlessly. This seldom-studied task faces two major challenges: 1) Preserving the head and body…
Interactive Feature Embedding for Infrared and Visible Image Fusion
Fan Zhao, Wenda Zhao, Huchuan Lu
General deep learning-based methods for infrared and visible image fusion rely on the unsupervised mechanism for vital information retention by utilizing elaborately designed loss…
Towards Grand Unification of Object Tracking
Bin Yan, Yi Jiang, Peize Sun +4
We present a unified method, termed Unicorn, that can simultaneously solve four tracking problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters. Due t…
SRRT: Exploring Search Region Regulation for Visual Object Tracking
Jiawen Zhu, Xin Chen, Pengyu Zhang +4
The dominant trackers generate a fixed-size rectangular region based on the previous prediction or initial bounding box as the model input, i.e., search region. While this manner o…
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling
Takashi Isobe, Xu Jia, Xin Tao +6
Temporal modeling is crucial for video super-resolution. Most of the video super-resolution methods adopt the optical flow or deformable convolution for explicitly motion compensat…
Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline
Pengyu Zhang, Jie Zhao, Dong Wang +2
With the popularity of multi-modal sensors, visible-thermal (RGB-T) object tracking is to achieve robust performance and wider application scenarios with the guidance of objects' t…
Deeply Interleaved Two-Stream Encoder for Referring Video Segmentation
Guang Feng, Lihe Zhang, Zhiwei Hu +1
Referring video segmentation aims to segment the corresponding video object described by the language expression. To address this task, we first design a two-stream encoder to extr…
TimeReplayer: Unlocking the Potential of Event Cameras for Video Interpolation
Weihua He, Kaichao You, Zhendong Qiao +6
Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted s…
Lane Detection with Versatile AtrousFormer and Local Semantic Guidance
Jiaxing Yang, Lihe Zhang, Huchuan Lu
Lane detection is one of the core functions in autonomous driving and has aroused widespread attention recently. The networks to segment lane instances, especially with bad appeara…
Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection
Youwei Pang, Xiaoqi Zhao, Tian-Zhu Xiang +2
The recently proposed camouflaged object detection (COD) attempts to segment objects that are visually blended into their surroundings, which is extremely complex and difficult in…
Efficient Visual Tracking via Hierarchical Cross-Attention Transformer
Xin Chen, Ben Kang, Dong Wang +2
In recent years, target tracking has made great progress in accuracy. This development is mainly attributed to powerful networks (such as transformers) and additional modules (such…
High-Performance Transformer Tracking
Xin Chen, Bin Yan, Jiawen Zhu +3
Correlation has a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion method that considers the s…
Joint Learning of Salient Object Detection, Depth Estimation and Contour Extraction
Xiaoqi Zhao, Youwei Pang, Lihe Zhang +1
Benefiting from color independence, illumination invariance and location discrimination attributed by the depth map, it can provide important supplemental information for extractin…