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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 0Source ↗Scholar ↗
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 0Source ↗Scholar ↗
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…