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Xinghao Pan

4 accepted papers

2024

HDPNERF: Hybrid Depth Priors for Neural Radiance Fields from Sparse Input Views

ICASSP 2024accepted

Neural Radiance Field (NeRF) shows a high prospect in the task of novel view synthesis. However, performance degrades drastically under limited input views since NeRF heavily relies on a large number of images to fit the geometry in scenes. Recent efforts focus on introducing extra constraints to im…

Cited by 0SourceScholar
2024

Improving Learned Video Compression by Exploring Spatial Redundancy

ICASSP 2024accepted

Learned video compression has developed rapidly and shown promising rate-distortion performance recently. Existing works have made great progress on removing temporal redundancy between inter-frames, while neglecting spatial redundancy within a frame. In this paper, we propose to explore spatial red…

Cited by 0SourceScholar
2016

Cyclades: Conflict-free Asynchronous Machine Learning

NeurIPS 2016poster

We present Cyclades, a general framework for parallelizing stochastic optimization algorithms in a shared memory setting. Cyclades is asynchronous during model updates, and requires no memory locking mechanisms, similar to Hogwild!-type algorithms. Unlike Hogwild!, Cyclades introduces no conflicts d…

2015

Parallel Correlation Clustering on Big Graphs

NeurIPS 2015poster

Given a similarity graph between items, correlation clustering (CC) groups similar items together and dissimilar ones apart. One of the most popular CC algorithms is KwikCluster: an algorithm that serially clusters neighborhoods of vertices, and obtains a 3-approximation ratio. Unfortunately, in pr…