We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the Jacobian of a differentiable renderer, which we instantiate to be a voxel radiance field.
In this paper, we present ExtremeBERT, a toolkit for accelerating and customizing BERT pretraining.
Ranked #1 on Sentence Classification on GLUE
Approximating radiance fields with volumetric grids is one of promising directions for improving NeRF, represented by methods like Plenoxels and DVGO, which achieve super-fast training convergence and real-time rendering.
In this paper, we present a novel method named MixVoxels to better represent the dynamic scenes with fast training speed and competitive rendering qualities.
In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO series.
Ranked #29 on Real-Time Object Detection on COCO
To this end, we propose a novel network named SuperFusion, exploiting the fusion of LiDAR and camera data at multiple levels.