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Found 10 papers, 4 papers with code
Boosting Diffusion Models with Moving Average Sampling in Frequency Domain
Diffusion models have recently brought a powerful revolution in image generation.
Revisiting Single Image Reflection Removal In the Wild
This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations.
Principled Knowledge Extrapolation with GANs
Human can extrapolate well, generalize daily knowledge into unseen scenarios, raise and answer counterfactual questions.
Freeform Body Motion Generation from Speech
Motivated by studies in linguistics, we decompose the co-speech motion into two complementary parts: pose modes and rhythmic dynamics.
Temporal Complementarity-Guided Reinforcement Learning for Image-to-Video Person Re-Identification
Image-to-video person re-identification aims to retrieve the same pedestrian as the image-based query from a video-based gallery set.
Image-To-Video Person Re-Identification
reinforcement-learning
+4
Bijective Mapping Network for Shadow Removal
Shadow removal, which aims to restore the background in the shadow regions, is challenging due to the highly ill-posed nature.
Radio-Assisted Human Detection
In this paper, we propose a radio-assisted human detection framework by incorporating radio information into the state-of-the-art detection methods, including anchor-based onestage detectors and two-stage detectors.
Contactless Electrocardiogram Monitoring with Millimeter Wave Radar
Specifically, we develop a millimeter-wave radar system to contactlessly measure cardiac mechanical activity and reconstruct ECG without any contact in.
Towards Domain-Independent and Real-Time Gesture Recognition Using mmWave Signal
To enhance the robustness of the system and reduce data collecting efforts, we design a data augmentation framework for mmWave signals based on correlations between signal patterns and gesture variations.
Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos
The key factor for video person re-identification is to effectively exploit both spatial and temporal clues from video sequences.
Ranked #10 on
Video Deinterlacing
on MSU Deinterlacer Benchmark
