7 citations · 20 across the 19 of their papers we have counts for
9 papers · 1 filter
Towards Real-World Burst Image Super-Resolution: Benchmark and Method
Pengxu Wei, Yujing Sun, Xingbei Guo +4
Despite substantial advances, single-image super-resolution (SISR) is always in a dilemma to reconstruct high-quality images with limited information from one input image, especial…
U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds
Yan Di, Chenyangguang Zhang, Ruida Zhang +6
In this paper, we propose U-RED, an Unsupervised shape REtrieval and Deformation pipeline that takes an arbitrary object observation as input, typically captured by RGB images or s…
WiCo: Win-win Cooperation of Bottom-up and Top-down Referring Image Segmentation
Zesen Cheng, Peng Jin, Hao Li +5
The top-down and bottom-up methods are two mainstreams of referring segmentation, while both methods have their own intrinsic weaknesses. Top-down methods are chiefly disturbed by…
Backdoor Attacks Against Incremental Learners: An Empirical Evaluation Study
Yiqi Zhong, Xianming Liu, Deming Zhai +2
Large amounts of incremental learning algorithms have been proposed to alleviate the catastrophic forgetting issue arises while dealing with sequential data on a time series. Howev…
Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning
Peng Jin, Jinfa Huang, Pengfei Xiong +5
Contrastive learning-based video-language representation learning approaches, e.g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined…
Multi-granularity Interaction Simulation for Unsupervised Interactive Segmentation
Kehan Li, Yian Zhao, Zhennan Wang +6
Interactive segmentation enables users to segment as needed by providing cues of objects, which introduces human-computer interaction for many fields, such as image editing and med…
Parallel Vertex Diffusion for Unified Visual Grounding
Zesen Cheng, Kehan Li, Peng Jin +4
Unified visual grounding pursues a simple and generic technical route to leverage multi-task data with less task-specific design. The most advanced methods typically present boxes…
DiffusionRet: Generative Text-Video Retrieval with Diffusion Model
Peng Jin, Hao Li, Zesen Cheng +5
Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i.e., p(candidates|query). While straightforward, thi…
UATVR: Uncertainty-Adaptive Text-Video Retrieval
Bo Fang, Wenhao Wu, Chang Liu +6
With the explosive growth of web videos and emerging large-scale vision-language pre-training models, e.g., CLIP, retrieving videos of interest with text instructions has attracted…