3 citations · 5 across the 4 of their papers we have counts for
4 papers
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…
Single-View View Synthesis with Self-Rectified Pseudo-Stereo
Yang Zhou, Hanjie Wu, Wenxi Liu +3
Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view vie…
Reducing Spatial Labeling Redundancy for Semi-supervised Crowd Counting
Yongtuo Liu, Sucheng Ren, Liangyu Chai +4
Labeling is onerous for crowd counting as it should annotate each individual in crowd images. Recently, several methods have been proposed for semi-supervised crowd counting to red…
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation
Yongtuo Liu, Dan Xu, Sucheng Ren +3
Due to domain shift, a large performance drop is usually observed when a trained crowd counting model is deployed in the wild. While existing domain-adaptive crowd counting methods…