General and Specific Effects of Stereo Learning

Technological advancements in virtual reality challenge the human vision, especially stereopsis, a function, which characterizes how two eyes coordinate to form a unified three-dimensional (3D) representation of the external world and is found to be deficient in 30% of the normal population. Although a few previous studies have consistently found that the perceptual learning of stereopsis significantly improved stereoacuity, an underlying mechanism of stereo learning remains heavily debated. Here, we trained subjects with normal stereo vision (assessed with the FLY Stereo Acuity Test) to judge stereopsis containing three types of binocular disparity orders (i.e., zero-, first-, and second-order), aiming to systematically examine the characteristics and plasticity of stereo learning. Thirty subjects were randomly assigned to the three training groups (each for the zero-, first-, or second-order disparity separately). The disparity thresholds were measured before and after training. The disparity threshold was measured in 10 additional control subjects only at the pre- and post-training phase. Stereoscopic images were displayed through a shutter goggle, which is synchronized to a monitor. We found that the training significantly improved the zero-, first-, and second-order disparity threshold by 52.42, 36.28, and 14.9% in the zero-order training condition; 30.44, 63.74, and 21.07% in the first-order training condition; and 30.77, 25.19, and 75.12% in the second-order training condition, respectively. There was no significant improvement in the control group. Interestingly, the greatest improvements in the first- and second-order disparity threshold were found in the corresponding disparity training group; on the contrary, the improvements in the zero-order disparity threshold were comparable across all the three disparity training groups. Our findings demonstrated both general (related to the zero-order disparity) and specific improvements (related to the first- and second-order disparity) in stereo learning, suggesting that stereo training occurs at different visual processing stages and its effects might depend on the specific training sites

Observation of gapless corner modes in synthetic translation dimensions

The introduction of synthetic dimensions in topological photonic systems enriches the exploration of topological phase of light in higher-dimensional space beyond three-dimensional real-space. Recently, the gapless corner modes of topological photonic crystals under translational deformation have been proposed, but their experimental observation is still absent. Here, we observe the gapless corner modes in a photonic crystal slab under translational deformation. The corner mode exhibits a frequency dependence that can be tuned through the translation of the slab. Importantly, we find that the existence of gapless corner modes is independent of the specific corner configuration. The gapless corner modes are experimentally imaged via the near-field scanning measurement, and validated numerically by full-wave simulations. Our work contributes to the advancement of topological photonics and provides valuable insights into the exploration of gapless corner modes in synthetic dimensions

Instance Brownian Bridge as Texts for Open-vocabulary Video Instance Segmentation

Temporally locating objects with arbitrary class texts is the primary pursuit of open-vocabulary Video Instance Segmentation (VIS). Because of the insufficient vocabulary of video data, previous methods leverage image-text pretraining model for recognizing object instances by separately aligning each frame and class texts, ignoring the correlation between frames. As a result, the separation breaks the instance movement context of videos, causing inferior alignment between video and text. To tackle this issue, we propose to link frame-level instance representations as a Brownian Bridge to model instance dynamics and align bridge-level instance representation to class texts for more precisely open-vocabulary VIS (BriVIS). Specifically, we build our system upon a frozen video segmentor to generate frame-level instance queries, and design Temporal Instance Resampler (TIR) to generate queries with temporal context from frame queries. To mold instance queries to follow Brownian bridge and accomplish alignment with class texts, we design Bridge-Text Alignment (BTA) to learn discriminative bridge-level representations of instances via contrastive objectives. Setting MinVIS as the basic video segmentor, BriVIS surpasses the Open-vocabulary SOTA (OV2Seg) by a clear margin. For example, on the challenging large-vocabulary VIS dataset (BURST), BriVIS achieves 7.43 mAP and exhibits 49.49% improvement compared to OV2Seg (4.97 mAP)

DiffusionRet: Generative Text-Video Retrieval with Diffusion Model

Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i.e., p(candidates|query). While straightforward, this de facto paradigm overlooks the underlying data distribution p(query), which makes it challenging to identify out-of-distribution data. To address this limitation, we creatively tackle this task from a generative viewpoint and model the correlation between the text and the video as their joint probability p(candidates,query). This is accomplished through a diffusion-based text-video retrieval framework (DiffusionRet), which models the retrieval task as a process of gradually generating joint distribution from noise. During training, DiffusionRet is optimized from both the generation and discrimination perspectives, with the generator being optimized by generation loss and the feature extractor trained with contrastive loss. In this way, DiffusionRet cleverly leverages the strengths of both generative and discriminative methods. Extensive experiments on five commonly used text-video retrieval benchmarks, including MSRVTT, LSMDC, MSVD, ActivityNet Captions, and DiDeMo, with superior performances, justify the efficacy of our method. More encouragingly, without any modification, DiffusionRet even performs well in out-domain retrieval settings. We believe this work brings fundamental insights into the related fields. Code is available at https://github.com/jpthu17/DiffusionRet.Comment: Accepted by ICCV 202

Short term effects of different omega-3 fatty acid formulation on lipid metabolism in mice fed high or low fat diet

BACKGROUND: Bioactivities of Docosahexaenoic acid (DHA) and Eicosapentaenoic acid (EPA) depend on their chemical forms. The present study was to investigate short term effects of triglyceride (TG), ethyl ester (EE), free fatty acid (FFA) and phospholipid (PL) forms of omega-3 fatty acid (FA) on lipid metabolism in mice, fed high fat or low fat diet. METHOD: Male Balb/c mice were fed with 0.7% different Omega-3 fatty acid formulation: DHA bound free fatty acid (DHA-FFA), DHA bound triglyceride (DHA-TG), DHA bound ethyl ester (DHA-EE) and DHA bound phospholipid (DHA-PL) for 1 week, with dietary fat levels at 5% and 22.5%. Serum and hepatic lipid concentrations were analyzed, as well as the fatty acid composition of liver and brain. RESULT: At low fat level, serum total cholesterol (TC) level in mice fed diets with DHA-FFA, DHA-EE and DHA-PL were significantly lower than that in the control group (P < 0.05). Hepatic TG level decreased significantly in mice fed diets with DHA-TG (P < 0.05), DHA-EE (P < 0.05) and DHA-PL (P < 0.05), while TC level in liver was significantly lower in mice fed diets with TG and EE compared with the control group (P < 0.05). At high fat level, mice fed diets with DHA-EE and DHA-PL had significantly lower hepatic TC level compared with the control diet (P < 0.05). Hepatic PL concentration experienced a significant increase in mice fed the diet with PL at high fat level (P < 0.05). Furthermore, both at low and high fat levels, hepatic DHA level significantly increased and AA level significantly decreased in all forms of DHA groups (P < 0.05), compared to control groups at two different fat levels, respectively. Additionally, cerebral DHA level in mice fed diets with DHA-FFA, DHA-EE and DHA-PL significantly increased compared with the control at high fat level (P < 0.05), but no significant differences were observed among dietary treatments for mice fed diets with low fat level. CONCLUSION: The present study suggested that not only total dietary fat content but also the molecular forms of omega-3 fatty acids contributed to lipid metabolism in mice. DHA-PL showed effective bioactivity in decreasing hepatic and serum TC, TG levels and increasing omega-3 concentration in liver and brain

Properties and Keplerian Rotation of the Hot Core IRAS 20126+4104

We present Submillimeter Array observations of the massive star-forming region IRAS 20126+4104 in the millimeter continuum and in several molecular line transitions. With the SMA data, we have detected nine molecular transitions, including DCN, CH3OH, H2CO, and HC3N molecules, and imaged each molecular line. From the 1.3 mm continuum emission a compact millimeter source is revealed, which is also associated with H2O, OH, and CH3OH masers. Using a rotation temperature diagram (RTD), we derive that the rotational temperature and the column density of CH3OH are 200 K and 3.7\times 1017 cm-2, respectively. The calculated results and analysis further indicate that a hot core coincides with IRAS 20126+4104. The position-velocity diagrams of H2CO 3(0,3)-2(0,2) and HC3N 25-24 clearly present Keplerian rotation. Moreover, H2CO 3(0,3)-2(0,2) is found to trace the disk rotation for the first time.Comment: 17 pages, 5 figures, accepted by Ap